Text-overlap comparison
This pair was found by matching on title alone (find_title_bucket_dupes.py) — the usual paragraph-embedding similarity search never generated a candidate for it at any threshold. The exhibits below are near-exact word-shingle matches instead — a multi-word verbatim run is the more convincing evidence of shared text than embedding similarity, with the matched span highlighted.
PAPER A
PAPER B
EARLIER¶53-58
information of the file will not be exposed to them. Therefore, we give the following security definition. Definition 4: We say a remote data integrity auditing scheme achieves sensitive information security if the sanitizer cannot derive the personal sensitive information of the file, besides the cloud and the shared users cannot derive any sensitive information of the file. IV. THE PROPOSED SCHEME A. An Overview In order to achieve data sharing with sensitive information hiding, we consider making use of the idea in the sanitizable signature [30] to sanitize the sensitive information of the file by introducing an authorized sanitizer. Nonetheless, it is infeasible if this sanitizable signature is directly used in remote data integrity auditing. Firstly, this signature in [30] is constructed based on chameleon hashes [31]. However, a lot of chameleon hashes exhibit the key exposure problem. To avoid this security problem, the signature used in [30] requires strongly unforgeable chameleon hashes, which will inevitable incur huge computation overhead [31]. Secondly, the signature used in [30] does not support blockless verifiability. It means that the verifier has to download the entire data from the cloud to verify the integrity of data, which will incur huge communication overhead and excessive verification time in big data storage scenario. Thirdly, the signature used in [30] is based on the PKI, which suffers from the complicated certificate management. In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 337 and then transforms their corresponding signatures into valid ones for sanitized file using transformation value. Finally, the sanitizer uploads the sanitized file and the corresponding signatures to the cloud. When the data integrity auditing task is performed, the cloud generates an auditing proof according to the challenge from the TPA. The TPA can verify the integrity of the sanitized file stored the cloud by checking whether this auditing proof is correct or not. The details will be described in the following subsection. B. Description of the Proposed Scheme In our scheme, an original file F is divided into n blocks (m1, m2, . . . , mn), where mi ∈Z∗ p denotes the i-th block of file F. Assume the user’s identity ID is l-bit, which is described as I D = (I D1, I D2, . . . , I Dl) ∈{0, 1}l. In previous remote data integrity auditing schemes [5], [12], a signature SSig is used to guarantee the integrity of the file identifier name. In our scheme, we also employ a similar identity-based signature SSig to guarantee the integrity of the file identifier name and the correctness of verification values. Assume ssk is the signing private key used to generate file tag in signature SSig and is held by user. Under such an assumption, our scheme is more clear and simple. Let K1 be the set of indexes of the data blocks corresponding to the personal sensitive information of the file F. Let K2 be the set of indexes of the data blocks corresponding to the organization’s sensitive information of the file F. In order to preserve the personal sensitive information of the file from the sanitizer, the data blocks whose indexes are in the set K1 should be blinded before the file is sent to the sanitizer. Assume the blinded file is
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶56-60
In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 337 and then transforms their corresponding signatures into valid ones for sanitized file using transformation value. Finally, the sanitizer uploads the sanitized file and the corresponding signatures to the cloud. When the data integrity auditing task is performed, the cloud generates an auditing proof according to the challenge from the TPA. The TPA can verify the integrity of the sanitized file stored the cloud by checking whether this auditing proof is correct or not. The details will be described in the following subsection. B. Description of the Proposed Scheme In our scheme, an original file F is divided into n blocks (m1, m2, . . . , mn), where mi ∈Z∗ p denotes the i-th block of file F. Assume the user’s identity ID is l-bit, which is described as I D = (I D1, I D2, . . . , I Dl) ∈{0, 1}l. In previous remote data integrity auditing schemes [5], [12], a signature SSig is used to guarantee the integrity of the file identifier name. In our scheme, we also employ a similar identity-based signature SSig to guarantee the integrity of the file identifier name and the correctness of verification values. Assume ssk is the signing private key used to generate file tag in signature SSig and is held by user. Under such an assumption, our scheme is more clear and simple. Let K1 be the set of indexes of the data blocks corresponding to the personal sensitive information of the file F. Let K2 be the set of indexes of the data blocks corresponding to the organization’s sensitive information of the file F. In order to preserve the personal sensitive information of the file from the sanitizer, the data blocks whose indexes are in the set K1 should be blinded before the file is sent to the sanitizer. Assume the blinded file is F∗= m∗ 1, m∗ 2, . . . , m∗ n which is different from the original file F= (m1, m2, . . . , mn) in index set K1. That is to say, mi = m∗ i only if i ∈[1, n] and i /∈K1; otherwise, mi̸ = m∗ i . To unify the format, the sanitizer needs to sanitize the blinded data blocks with wildcards. Furthermore, to protect the privacy of organization, the sanitizer also needs to sanitize the data blocks corresponding to the organization’s sensitive information. The sanitized file is F′= m′
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶132-136
n )c ≤PX ≤1 −( n−c+1−k n−c+1 )c, since n−i−1−k n−i−1 ≤ n−i−k n−i . Thus, we can conclude that the proposed scheme can detect the misbehavior of the cloud with probability at least 1 − n−k n c. Theorem 4: (Sensitive information hiding) The sanitizer cannot derive the personal sensitive information of the file, besides the cloud and the shared users cannot derive any sensitive information of the file in our scheme. Proof: (1) In our scheme, the user needs to blind the data blocks corresponding to the personal sensitive information of the original file F before sending this file to the sanitizer. Because the blinding factors αi = fk1(i, name)(i ∈K1) are randomly generated by the user, the blinded data blocks m∗ i = mi + αi (i ∈K1) of F∗received by the sanitizer are unpredictable. Therefore, the sanitizer cannot know the real data blocks mi (i ∈K1) according to the blinded data blocks m∗ i = mi + αi (i ∈K1) from the user. That is to say, the sanitizer cannot derive the personal sensitive information from F∗it received. (2) After receiving the blinded file F∗, the sanitizer sanitizes the data blocks corresponding to the personal sensitive
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶142-146
Ex pG2 respectively denote one multiplication operation and one exponentiation operation in G2. n is the total number of data blocks. c is the number of challenged data blocks. d1 is the number of data blocks corresponding to the personal sensitive information. d2 is the number of data blocks corresponding to the organization’s sensitive information. l is the length of user identify. |n| is the size of an element of set [1, n], |p| is the size of an element in Z∗ p, and |q| is the size of an element in G1. SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 343 TABLE III THE COMPUTATION OVERHEAD OF OUR SCHEME AND SHACHAM ET AL. SCHEME [4] IN DIFFERENT PHASES 1) Computation overhead comparison. In Table III, we give the computation overhead comparison between our scheme and Shacham and Waters scheme [4] in different phases. From Section IV, we can know that, before sending the original file to the sanitizer, the user needs to blind the data blocks corresponding to the personal sensitive information of the file. The computation overhead of data blinding is d1AddZ∗ p. And then the user generates the signatures for the blinded file. The computation overhead of computing signatures is n(HashG1 +2MulG1 +2Ex pG1). The sanitizer sanitizes the blinded data blocks and the data blocks corresponding to the organization’s sensitive information, and transforms the signatures of these data blocks into valid ones for the sanitized file. In the phase of sanitization, the computation overhead on the sanitizer side is (d1 + d2)(Ex pG1 + MulG1 + SubZ∗p). In the phase of integrity auditing, the TPA firstly needs to generate and send an auditing challenge to the cloud, which only costs negligible computation overhead. And then, the cloud outputs an auditing proof P = {λ, σ} to reply the TPA. The computation overhead of the cloud is (c−1)MulG1+cEx pG1+cMulZ∗p+(c−1)AddZ∗p. When the TPA verifies this auditing proof, the computation overhead of the TPA is 4 Pair + 2MulG2 + 2(c − 1)AddZ∗p +2Ex pG2+(l+c+1)Ex pG1+(c+l)MulG1 + cHashG1. The construction of the scheme [4] is generally regarded as one of the most efficient one among all existing remote data integrity auditing schemes. In this scheme [4], one data block is divided into multiple sectors, which can reduce storage overhead. Actually, our scheme also can support multiple sectors. But for simplification, we only consider the situation that the file F is divided into n data blocks, and do not consider the situation that each data block is divided into s sectors. For fairness comparison, we set s = 1 in scheme [4]. As shown in Table III, we can see that our scheme and the scheme [4] have almost the same computation overhead in the phase of signature generation. It means that our scheme and the scheme [4] have the same efficiency when processing the same file. In the phase of proof generation, the cloud’s computation overhead in our scheme and the scheme [4] are the same. For the TABLE IV THE COMMUNICATION OVERHEAD OF THE PROPOSED SCHEME TABLE V THE COMPUTATION COMPLEXITY OF DIFFERENT ENTITIES IN DIFFERENT PHASES TPA in the phase of proof verification, our scheme costs more computation overhead than the scheme [4]. On the other hand, as Table II shows, our scheme can satisfy the following properties: data sharing, sensitive information hiding and certificate management simplification. However, the scheme [4] cannot satisfy the above properties. Therefore, the above comparison shows that our scheme has the same efficiency level with the scheme [4], but meets more properties. 2) Communication overhead. According to the description of Section IV, we can know that the communication overhead of the proposed scheme is mainly from the integrity auditing phase, as shown in Table IV. Thus, we only consider the communication overhead incurred in the remote data integrity auditing. In the phase of integrity auditing, the TPA sends an auditing challenge chal = {i, vi}i∈I to the cloud. The size of an auditing challenge is c · (|n| + |p|) bits. After receiving the auditing challenge from the TPA, the cloud generates an auditing proof P = {λ, σ} to reply the TPA. The size of an auditing proof P = {λ, σ} is |p| + |q| bits. Therefore, for one auditing task, the whole communication overhead is c · |n| + (c + 1) · |p| + |q| bits. 3) Computation complexity. We analyze the computation complexity of the different entities in different phases in Table V. The computation complexity of different
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶68-72
I D, sk′′ I D) = (g2x · (μ′ l j=1 μ j I D j )rI D, grI D) as the private key of the user ID. The PKG sends it to the user ID. b) The user ID verifies the correctness of the received private key skI D by checking whether the following equation holds or not. e(sk′ I D, g) = (g1, g2) · e(μ′ l j=1 μ j I D j , sk′′ I D). (1) If above equation does not hold, the user ID refuses the private key skI D; otherwise, accepts it. 3) Algorithm SigGen(F, skID, ssk, name) The process is illustrated in Fig. 4. a) The user ID randomly chooses a value r ∈Z∗ p, and calculates a verification value gr. Then the user ID randomly chooses a seed k1 ∈Z∗ p as the input secret key of pseudo-random function f. The user ID employs the secret seed k1 to calculate the blinding factor αi = fk1(i, name)(i ∈K1) which is used to blind the data blocks corresponding to the personal sensitive information, where name ∈Z∗ p is a random value chosen as the file identifier. b) In order to preserve the personal sensitive informa- tion from the sanitizer, the user ID should blind the data blocks corresponding to the personal sensitive information of the original file F before sending it to the sanitizer. The indexes of these data blocks are in set K1. The user ID computes the blinded data block m∗ i = mi + αi for each block mi ∈Z∗ p (i ∈K1) of the original file F. The blinded file is F∗= m∗ 1, m∗ 2, . . . , m∗ n , where m∗ i = mi only if i ∈[1, n] and i /∈K1; otherwise, m∗
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶69-73
private key skI D by checking whether the following equation holds or not. e(sk′ I D, g) = (g1, g2) · e(μ′ l j=1 μ j I D j , sk′′ I D). (1) If above equation does not hold, the user ID refuses the private key skI D; otherwise, accepts it. 3) Algorithm SigGen(F, skID, ssk, name) The process is illustrated in Fig. 4. a) The user ID randomly chooses a value r ∈Z∗ p, and calculates a verification value gr. Then the user ID randomly chooses a seed k1 ∈Z∗ p as the input secret key of pseudo-random function f. The user ID employs the secret seed k1 to calculate the blinding factor αi = fk1(i, name)(i ∈K1) which is used to blind the data blocks corresponding to the personal sensitive information, where name ∈Z∗ p is a random value chosen as the file identifier. b) In order to preserve the personal sensitive informa- tion from the sanitizer, the user ID should blind the data blocks corresponding to the personal sensitive information of the original file F before sending it to the sanitizer. The indexes of these data blocks are in set K1. The user ID computes the blinded data block m∗ i = mi + αi for each block mi ∈Z∗ p (i ∈K1) of the original file F. The blinded file is F∗= m∗ 1, m∗ 2, . . . , m∗ n , where m∗ i = mi only if i ∈[1, n] and i /∈K1; otherwise, m∗ i̸ = mi. c) For each block m∗ i ∈ Z∗ p (i ∈ [1, n]) of the blinded file F∗, the user ID calculates 338 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 14, NO. 2, FEBRUARY 2019
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
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332 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 14, NO. 2, FEBRUARY 2019 this encrypted file, finally upload this encrypted file and its corresponding signatures to the cloud. This method can realize the sensitive information hiding since only the data owner can decrypt this file. However, it will make the whole shared file unable to be used by others. For example, encrypting the EHRs of infectious disease patients can protect the privacy of patient and hospital, but these encrypted EHRs cannot be effectively utilized by researchers any more. Distributing the decryption key to the researchers seems to be a possible solution to the above problem. However, it is infeasible to adopt this method in real scenarios due to the following reasons. Firstly, distributing decryption key needs secure channels, which is hard to be satisfied in some instances. Furthermore, it seems very difficult for a user to know which researchers will use his/her EHRs in the near future when he/she uploads the EHRs to the cloud. As a result, it is impractical to hide sensitive information by encrypting the whole shared file. Thus, how to realize data sharing with sensitive information hiding in remote data integrity auditing is very important and valuable. Unfortunately, this problem has remained unexplored in previous researches. Contribution The contribution of this paper can be summarized as follows: (1) We investigate how to achieve data sharing with sensitive information hiding in remote data integrity auditing, and propose a new concept called identity-based shared data integrity auditing with sensitive information hiding for secure cloud storage. In such a scheme, the sensitive information can be protected and the other information can be published. It makes the file stored in the cloud able to be shared and used by others on the condition that the sensitive information is protected, while the remote data integrity auditing is still able to be efficiently executed. (2) We design a practical identity-based shared data integrity auditing scheme with sensitive information hiding for secure cloud storage. A sanitizer is used to sanitize the data blocks corresponding to the sensitive information of the file. In our detailed scheme, firstly, the user blinds the data blocks corresponding to the personal sensitive information of the original file and generates the corresponding signatures, and then sends them to a sanitizer. The sanitizer sanitizes these blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information. It also transforms the corresponding signatures into valid ones for the sanitized file. This method not only realizes the remote data integrity auditing, but also supports the data sharing on the condition that sensitive information is protected in cloud storage. To the best of our knowledge, this is the first scheme with the above functions. Besides, our scheme is based on identity-based cryptography, which simplifies the complex certificate management. (3) We give the security analysis of the proposed scheme, and also justify the performance by concrete implementations. The result shows that the proposed scheme achieves desirable security and efficiency. Fig. 1. Example of EHRs. A. An Illustrative Example for EHRs Here, we give an illustrative example for EHRs in Fig. 1. In this example, the sensitive information of EHRs contains two parts. One is the personal sensitive information (patient’s sensitive information), such as patient’s name and patient’s ID number. The other is the organization’s sensitive information (hospital’s sensitive information), such as the hospital’s name.∗Generally speaking, the above sensitive information should be replaced with wildcards when the EHRs are uploaded to cloud for research purpose. The sanitizer can be viewed as the administrator of the EHR information system in a hospital. The personal sensitive information should not be exposed to the sanitizer. And all of the sensitive information should not be exposed to the cloud and the shared users. A medical doctor needs to generate and send the EHRs of patients to the sanitizer for storing them in the EHR information system. However, these EHRs usually contain the sensitive information of patient and hospital, such as patient’s name, patient’s ID number and hospital’s name. To preserve the privacy of patient from the sanitizer, the medical doctor will blind the patient’s sensitive information of each EHR before sending this EHR to the sanitizer. The medical doctor then generates signatures for this blinded EHR and sends them to the sanitizer. The sanitizer stores these messages into EHR information system. When the medical doctor needs the EHR, he sends a request to the sanitizer. And then the sanitizer downloads the blinded EHR from the EHR information system and sends it to the medical doctor. Finally, the medical doctor recovers the original EHR from this blinded EHR. When this EHR needs to be uploaded and shared in the cloud for research purpose, in order to unify the format, the sanitizer needs to sanitize the data blocks corresponding to the patient’s sensitive information of the EHR. In addition, to protect the privacy of hospital, the sanitizer needs to sanitize the data blocks corresponding to the hospital’s sensitive information.
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
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(2) User: The user is a member of an organization, which has a large number of files to be stored in the cloud. (3) Sanitizer: The sanitizer is in charge of sanitizing the data blocks corresponding to the sensitive information (personal sensitive information and the organization’s sensitive information) in the file, transforming these data blocks’ signatures into valid ones for the sanitized file, and uploading the sanitized file and its corresponding signatures to the cloud. (4) PKG: The PKG is trusted by other entities. It is responsible for generating system public parameters and the private key for the user according to his identity ID. (5) TPA: The TPA is a public verifier. It is in charge of verifying the integrity of the data stored in the cloud on behalf of users. The user firstly blinds the data blocks corresponding to the personal sensitive information of the file, and generates the corresponding signatures. These signatures are used to guarantee the authenticity of the file and verify the integrity of the file. Then the user sends this blinded file and its corresponding signatures to the sanitizer. After receiving the message from the user, the sanitizer sanitizes these blinded data blocks and the data blocks corresponding to the organization’s sensitive information, and then transforms the signatures of sanitized data blocks into valid ones for the sanitized file. Finally, the sanitizer sends this sanitized file and its corresponding signatures to the cloud. These signatures are used to verify the integrity of the sanitized file in the phase of integrity auditing. When the TPA wants to verify the integrity of the sanitized file stored in the cloud, he sends an auditing challenge to the cloud. And then, the cloud responds to the TPA with an auditing proof of data possession. Finally, the TPA verifies the integrity of the sanitized file by checking whether this auditing proof is correct or not. B. Design Goals To efficiently support data sharing with sensitive information hiding in identity-based integrity auditing for secure cloud storage, our scheme is designed to achieve the following goals:
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶56-60
In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 337 and then transforms their corresponding signatures into valid ones for sanitized file using transformation value. Finally, the sanitizer uploads the sanitized file and the corresponding signatures to the cloud. When the data integrity auditing task is performed, the cloud generates an auditing proof according to the challenge from the TPA. The TPA can verify the integrity of the sanitized file stored the cloud by checking whether this auditing proof is correct or not. The details will be described in the following subsection. B. Description of the Proposed Scheme In our scheme, an original file F is divided into n blocks (m1, m2, . . . , mn), where mi ∈Z∗ p denotes the i-th block of file F. Assume the user’s identity ID is l-bit, which is described as I D = (I D1, I D2, . . . , I Dl) ∈{0, 1}l. In previous remote data integrity auditing schemes [5], [12], a signature SSig is used to guarantee the integrity of the file identifier name. In our scheme, we also employ a similar identity-based signature SSig to guarantee the integrity of the file identifier name and the correctness of verification values. Assume ssk is the signing private key used to generate file tag in signature SSig and is held by user. Under such an assumption, our scheme is more clear and simple. Let K1 be the set of indexes of the data blocks corresponding to the personal sensitive information of the file F. Let K2 be the set of indexes of the data blocks corresponding to the organization’s sensitive information of the file F. In order to preserve the personal sensitive information of the file from the sanitizer, the data blocks whose indexes are in the set K1 should be blinded before the file is sent to the sanitizer. Assume the blinded file is F∗= m∗ 1, m∗ 2, . . . , m∗ n which is different from the original file F= (m1, m2, . . . , mn) in index set K1. That is to say, mi = m∗ i only if i ∈[1, n] and i /∈K1; otherwise, mi̸ = m∗ i . To unify the format, the sanitizer needs to sanitize the blinded data blocks with wildcards. Furthermore, to protect the privacy of organization, the sanitizer also needs to sanitize the data blocks corresponding to the organization’s sensitive information. The sanitized file is F′= m′
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶11-15
332 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 14, NO. 2, FEBRUARY 2019 this encrypted file, finally upload this encrypted file and its corresponding signatures to the cloud. This method can realize the sensitive information hiding since only the data owner can decrypt this file. However, it will make the whole shared file unable to be used by others. For example, encrypting the EHRs of infectious disease patients can protect the privacy of patient and hospital, but these encrypted EHRs cannot be effectively utilized by researchers any more. Distributing the decryption key to the researchers seems to be a possible solution to the above problem. However, it is infeasible to adopt this method in real scenarios due to the following reasons. Firstly, distributing decryption key needs secure channels, which is hard to be satisfied in some instances. Furthermore, it seems very difficult for a user to know which researchers will use his/her EHRs in the near future when he/she uploads the EHRs to the cloud. As a result, it is impractical to hide sensitive information by encrypting the whole shared file. Thus, how to realize data sharing with sensitive information hiding in remote data integrity auditing is very important and valuable. Unfortunately, this problem has remained unexplored in previous researches. Contribution The contribution of this paper can be summarized as follows: (1) We investigate how to achieve data sharing with sensitive information hiding in remote data integrity auditing, and propose a new concept called identity-based shared data integrity auditing with sensitive information hiding for secure cloud storage. In such a scheme, the sensitive information can be protected and the other information can be published. It makes the file stored in the cloud able to be shared and used by others on the condition that the sensitive information is protected, while the remote data integrity auditing is still able to be efficiently executed. (2) We design a practical identity-based shared data integrity auditing scheme with sensitive information hiding for secure cloud storage. A sanitizer is used to sanitize the data blocks corresponding to the sensitive information of the file. In our detailed scheme, firstly, the user blinds the data blocks corresponding to the personal sensitive information of the original file and generates the corresponding signatures, and then sends them to a sanitizer. The sanitizer sanitizes these blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information. It also transforms the corresponding signatures into valid ones for the sanitized file. This method not only realizes the remote data integrity auditing, but also supports the data sharing on the condition that sensitive information is protected in cloud storage. To the best of our knowledge, this is the first scheme with the above functions. Besides, our scheme is based on identity-based cryptography, which simplifies the complex certificate management. (3) We give the security analysis of the proposed scheme, and also justify the performance by concrete implementations. The result shows that the proposed scheme achieves desirable security and efficiency. Fig. 1. Example of EHRs. A. An Illustrative Example for EHRs Here, we give an illustrative example for EHRs in Fig. 1. In this example, the sensitive information of EHRs contains two parts. One is the personal sensitive information (patient’s sensitive information), such as patient’s name and patient’s ID number. The other is the organization’s sensitive information (hospital’s sensitive information), such as the hospital’s name.∗Generally speaking, the above sensitive information should be replaced with wildcards when the EHRs are uploaded to cloud for research purpose. The sanitizer can be viewed as the administrator of the EHR information system in a hospital. The personal sensitive information should not be exposed to the sanitizer. And all of the sensitive information should not be exposed to the cloud and the shared users. A medical doctor needs to generate and send the EHRs of patients to the sanitizer for storing them in the EHR information system. However, these EHRs usually contain the sensitive information of patient and hospital, such as patient’s name, patient’s ID number and hospital’s name. To preserve the privacy of patient from the sanitizer, the medical doctor will blind the patient’s sensitive information of each EHR before sending this EHR to the sanitizer. The medical doctor then generates signatures for this blinded EHR and sends them to the sanitizer. The sanitizer stores these messages into EHR information system. When the medical doctor needs the EHR, he sends a request to the sanitizer. And then the sanitizer downloads the blinded EHR from the EHR information system and sends it to the medical doctor. Finally, the medical doctor recovers the original EHR from this blinded EHR. When this EHR needs to be uploaded and shared in the cloud for research purpose, in order to unify the format, the sanitizer needs to sanitize the data blocks corresponding to the patient’s sensitive information of the EHR. In addition, to protect the privacy of hospital, the sanitizer needs to sanitize the data blocks corresponding to the hospital’s sensitive information.
LATER¶3-7
khutaija@lords.ac.in Abstract— Cloud storage services enable users to outsource data and share it remotely, but ensuring both integrity and privacy of sensitive information remains a critical challenge. Traditional remote data integrity auditing verifies correctness of stored files; however, in applications such as Electronic Health Records (EHRs), directly sharing files risks exposing confidential data, while encrypting entire files hides sensitive content but limits usability. To overcome this, we propose an identity-based remote data integrity auditing scheme that integrates sensitive information hiding with secure data sharing. The approach employs a sanitizer to replace sensitive data blocks with sanitized versions and transform their signatures into valid ones, enabling integrity verification without revealing hidden content. Additionally, proxy re-signatures facilitate efficient and secure user revocation, while a blockchain-based decentralized auditing process eliminates reliance on a trusted third party, thereby enhancing transparency and reliability. Security and performance evaluations demonstrate that the proposed scheme achieves strong privacy preservation, reduced computational overhead, and practical efficiency for realworld cloud storage applications. Index Terms— Cloud storage; Remote integrity auditing; Data sharing; Privacy preservation; Identity-based cryptography; Blockchain. I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving
EARLIER¶17-21
SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 333 Generally, these data blocks are replaced with wildcards. Furthermore, the sanitizer can transform these data blocks’ signatures into valid ones for the sanitized EHR. It makes the remote data integrity auditing still able to be effectively performed. During the process of sanitization, the sanitizer does not need to interact with medical doctors. Finally, the sanitizer uploads these sanitized EHRs and their corresponding signatures to the cloud. In this way, the EHRs can be shared and used by researchers, while the sensitive information of EHRs can be hidden. Meanwhile, the integrity of these EHRs stored in the cloud can be ensured. The sanitizer is necessary because of the following reasons. Firstly, after the data blocks corresponding to the patient’s sensitive information are blinded, the contents of these data blocks might become messy code. The sanitizer can unify the format by using wildcards to replace the contents of these data blocks. In addition, the sanitizer also can sanitize the data blocks corresponding to the hospital’s sensitive information such as hospital’s name by using wildcards, which protects the privacy of the hospital. Secondly, the sanitizer can facilitate the information management. It can sanitize the EHRs in bulk, and uploads these sanitized EHRs to the cloud at a fixed time. Thirdly, when the medical doctor needs the EHR, the sanitizer as the administrator of EHR information system can download the blinded EHR from the EHR information system and sends it to the medical doctor. The medical doctor can recover the original EHR from the blinded one. B. Related Work In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomorphic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in [5]. To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation technique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. To reduce the damage of users’ key exposure, Yu et al. [13] and [14], and Yu and Wang [15] proposed key-exposure resilient remote data integrity auditing schemes based on key update technique [16].
LATER¶4-8
I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in.To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation tech nique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree.
EARLIER¶6-10
Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIFS.2018.2850312 the complicated certificate management. The security analysis and the performance evaluation show that the proposed scheme is secure and efficient. Index Terms—Cloud storage, data integrity auditing, data sharing, sensitive information hiding. I. INTRODUCTION W ITH the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud [1]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed [2]–[8]. In remote data integrity auditing schemes, the data owner firstly needs to generate signatures for data blocks before uploading them to the cloud. These signatures are used to prove the cloud truly possesses these data blocks in the phase of integrity auditing. And then the data owner uploads these data blocks along with their corresponding signatures to the cloud. The data stored in the cloud is often shared across multiple users in many cloud storage applications, such as Google Drive, Dropbox and iCloud. Data sharing as one of the most common features in cloud storage, allows a number of users to share their data with others. However, these shared data stored in the cloud might contain some sensitive information. For instance, the Electronic Health Records (EHRs) [9] stored and shared in the cloud usually contain patients’ sensitive information (patient’s name, telephone number and ID number, etc.) and the hospital’s sensitive information (hospital’s name, etc.). If these EHRs are directly uploaded to the cloud to be shared for research purposes, the sensitive information of patient and hospital will be inevitably exposed to the cloud and the researchers. Besides, the integrity of the EHRs needs to be guaranteed due to the existence of human errors and software/hardware failures in the cloud. Therefore, it is important to accomplish remote data integrity auditing on the condition that the sensitive information of shared data is protected. 1556-6013 © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
LATER¶4-8
I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in.To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation tech nique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree.
EARLIER¶17-22
SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 333 Generally, these data blocks are replaced with wildcards. Furthermore, the sanitizer can transform these data blocks’ signatures into valid ones for the sanitized EHR. It makes the remote data integrity auditing still able to be effectively performed. During the process of sanitization, the sanitizer does not need to interact with medical doctors. Finally, the sanitizer uploads these sanitized EHRs and their corresponding signatures to the cloud. In this way, the EHRs can be shared and used by researchers, while the sensitive information of EHRs can be hidden. Meanwhile, the integrity of these EHRs stored in the cloud can be ensured. The sanitizer is necessary because of the following reasons. Firstly, after the data blocks corresponding to the patient’s sensitive information are blinded, the contents of these data blocks might become messy code. The sanitizer can unify the format by using wildcards to replace the contents of these data blocks. In addition, the sanitizer also can sanitize the data blocks corresponding to the hospital’s sensitive information such as hospital’s name by using wildcards, which protects the privacy of the hospital. Secondly, the sanitizer can facilitate the information management. It can sanitize the EHRs in bulk, and uploads these sanitized EHRs to the cloud at a fixed time. Thirdly, when the medical doctor needs the EHR, the sanitizer as the administrator of EHR information system can download the blinded EHR from the EHR information system and sends it to the medical doctor. The medical doctor can recover the original EHR from the blinded one. B. Related Work In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomorphic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in [5]. To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation technique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. To reduce the damage of users’ key exposure, Yu et al. [13] and [14], and Yu and Wang [15] proposed key-exposure resilient remote data integrity auditing schemes based on key update technique [16]. The data sharing is an important application in cloud storage scenarios. To protect the identity privacy of user, Wang et al. [17] designed a privacy-preserving shared data integrity auditing scheme by modifying the ring signature for secure cloud storage. Yang et al. [18] constructed an efficient shared data integrity auditing scheme, which not only supports the identity privacy but only achieves the identity traceability of users. Fu et al. [19] designed a privacy-aware shared data integrity auditing scheme by exploiting a homomorphic verifiable group signature. In order to support efficient user revocation, Wang et al. [20] proposed a shared data integrity auditing scheme with user revocation by using the proxy re-signature. With the employment of the Shamir secret sharing technique, Luo et al. [21] constructed a shared data integrity auditing scheme supporting user revocation.
LATER¶4-10
I. INTRODUCTION With the rapid expansion of data volumes, storing massive datasets locally has become increasingly impractical for users. As a result, both individuals and organizations are increasingly opting to outsource their data storage to cloud environments. Nevertheless, data stored in the cloud remains vulnerable to corruption or loss caused by unavoidable factors such as software defects, hardware failures, or human errors [1]. To ensure the correctness and reliability of outsourced data, numerous remote data integrity auditing mechanisms have been developed and widely studied [2][3]. In remote data integrity auditing frameworks, the data owner initially generates cryptographic signatures for individual data blocks prior to uploading them to the cloud. These signatures serve as proofs during the auditing phase, ensuring that the cloud indeed retains the corresponding data blocks. Once generated, both the data blocks and their associated signatures are uploaded to the cloud server. In practical cloud storage platforms such as Google Drive, Dropbox, and iCloud, stored data is frequently shared among multiple users. Data sharing, being a fundamental functionality of cloud services, enables users to provide access to their files with others. However, shared datasets often contain sensitive information that must be protected—for example, Electronic Health Records (EHRs) [4] II. PROBLEM DEFINITION In order to address above problems, we design a new efficient signature algorithm in the phase of signature generation. The designed signature scheme supports blockless verifiability, which allows the verifier to check the integrity of data without downloading the entire data from the cloud. In addition, it is based on identity-based cryptography, which simplifies the complicated certificate management. In our proposed scheme, the PKG generates the private key for user according to his identity ID. The user can check the correctness of the received private key. When there is a desire for the user to upload data to the cloud, in order to preserve the personal sensitive information of the original file from the sanitizer, this user needs to use a blinding factor to blind the data blocks corresponding to the personal sensitive information of the original file. When necessary, the user can recover the original file from the blinded one by using this blinding factor. And then this user employs the designed signature algorithm to generate signatures for the blinded file. These signatures will be used to verify the integrity of this blinded file. In addition, the user generates a file tag, which is used to ensure the correctness of the file identifier name and some verification values. The user also computes a transformation value that is used to transform signatures for sanitizer. Finally, the user sends the blinded file, its corresponding signatures, and the file tag along with the transformation value to the sanitizer. When the above messages from user are valid, the sanitizer firstly sanitizes the blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information to protect the privacy of organization, III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in.To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation tech nique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. Using cloud storage, users can remotely store their data and enjoy the on-demand high-quality applications and services from a shared pool of configurable computing resources, without the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in cloud computing a formidable task, especially for users with constrained computing resources. Moreover, users should be able to just use the cloud storage as if it is local, without worrying about the need to verify its integrity. Thus, enabling public auditability for cloud storage is of critical importance so that users can resort to a third-party auditor (TPA) to check the integrity of outsourced data and be worry free. To securely introduce an effective TPA, the auditing process should bring in no new vulnerabilities toward user data privacy, and introduce no additional online burden to user. In this paper, we propose a secure cloud storage system supporting privacy-preserving public auditing. We further extend our result to enable the TPA to perform audits for multiple users simultaneously and efficiently. Extensive security and performance analysis show the proposed schemes are provably secure and highly efficient. Our preliminary experiment conducted on Amazon EC2 instance further demonstrates the fast performance of the design. To enable data sharing while concealing sensitive information, we adopt the concept of sanitizable signatures [10], whereby an authorized sanitizer is introduced to sanitize the sensitive portions of a file. However, directly applying this technique in remote data integrity auditing is impractical. First, the construction in relies on chameleon hashes, many of which suffer from key exposure vulnerabilities. To mitigate this issue, the scheme requires the use of strongly unforgeable chameleon hashes, which significantly increases computational costs [11]. Second, the signature scheme in lacks support for blockless verifiability, meaning that a verifier must retrieve the entire dataset from the cloud to check its integrity. This approach leads to excessive communication overhead and high verification latency, particularly in large-scale storage scenarios. Third, the scheme depends on a Public Key Infrastructure (PKI), which introduces the additional burden of complex certificate management.
EARLIER¶18-22
The sanitizer is necessary because of the following reasons. Firstly, after the data blocks corresponding to the patient’s sensitive information are blinded, the contents of these data blocks might become messy code. The sanitizer can unify the format by using wildcards to replace the contents of these data blocks. In addition, the sanitizer also can sanitize the data blocks corresponding to the hospital’s sensitive information such as hospital’s name by using wildcards, which protects the privacy of the hospital. Secondly, the sanitizer can facilitate the information management. It can sanitize the EHRs in bulk, and uploads these sanitized EHRs to the cloud at a fixed time. Thirdly, when the medical doctor needs the EHR, the sanitizer as the administrator of EHR information system can download the blinded EHR from the EHR information system and sends it to the medical doctor. The medical doctor can recover the original EHR from the blinded one. B. Related Work In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomorphic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in [5]. To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation technique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. To reduce the damage of users’ key exposure, Yu et al. [13] and [14], and Yu and Wang [15] proposed key-exposure resilient remote data integrity auditing schemes based on key update technique [16]. The data sharing is an important application in cloud storage scenarios. To protect the identity privacy of user, Wang et al. [17] designed a privacy-preserving shared data integrity auditing scheme by modifying the ring signature for secure cloud storage. Yang et al. [18] constructed an efficient shared data integrity auditing scheme, which not only supports the identity privacy but only achieves the identity traceability of users. Fu et al. [19] designed a privacy-aware shared data integrity auditing scheme by exploiting a homomorphic verifiable group signature. In order to support efficient user revocation, Wang et al. [20] proposed a shared data integrity auditing scheme with user revocation by using the proxy re-signature. With the employment of the Shamir secret sharing technique, Luo et al. [21] constructed a shared data integrity auditing scheme supporting user revocation.
LATER¶6-10
III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in.To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation tech nique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. Using cloud storage, users can remotely store their data and enjoy the on-demand high-quality applications and services from a shared pool of configurable computing resources, without the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in cloud computing a formidable task, especially for users with constrained computing resources. Moreover, users should be able to just use the cloud storage as if it is local, without worrying about the need to verify its integrity. Thus, enabling public auditability for cloud storage is of critical importance so that users can resort to a third-party auditor (TPA) to check the integrity of outsourced data and be worry free. To securely introduce an effective TPA, the auditing process should bring in no new vulnerabilities toward user data privacy, and introduce no additional online burden to user. In this paper, we propose a secure cloud storage system supporting privacy-preserving public auditing. We further extend our result to enable the TPA to perform audits for multiple users simultaneously and efficiently. Extensive security and performance analysis show the proposed schemes are provably secure and highly efficient. Our preliminary experiment conducted on Amazon EC2 instance further demonstrates the fast performance of the design. To enable data sharing while concealing sensitive information, we adopt the concept of sanitizable signatures [10], whereby an authorized sanitizer is introduced to sanitize the sensitive portions of a file. However, directly applying this technique in remote data integrity auditing is impractical. First, the construction in relies on chameleon hashes, many of which suffer from key exposure vulnerabilities. To mitigate this issue, the scheme requires the use of strongly unforgeable chameleon hashes, which significantly increases computational costs [11]. Second, the signature scheme in lacks support for blockless verifiability, meaning that a verifier must retrieve the entire dataset from the cloud to check its integrity. This approach leads to excessive communication overhead and high verification latency, particularly in large-scale storage scenarios. Third, the scheme depends on a Public Key Infrastructure (PKI), which introduces the additional burden of complex certificate management.
EARLIER¶18-23
The sanitizer is necessary because of the following reasons. Firstly, after the data blocks corresponding to the patient’s sensitive information are blinded, the contents of these data blocks might become messy code. The sanitizer can unify the format by using wildcards to replace the contents of these data blocks. In addition, the sanitizer also can sanitize the data blocks corresponding to the hospital’s sensitive information such as hospital’s name by using wildcards, which protects the privacy of the hospital. Secondly, the sanitizer can facilitate the information management. It can sanitize the EHRs in bulk, and uploads these sanitized EHRs to the cloud at a fixed time. Thirdly, when the medical doctor needs the EHR, the sanitizer as the administrator of EHR information system can download the blinded EHR from the EHR information system and sends it to the medical doctor. The medical doctor can recover the original EHR from the blinded one. B. Related Work In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomorphic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in [5]. To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation technique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. To reduce the damage of users’ key exposure, Yu et al. [13] and [14], and Yu and Wang [15] proposed key-exposure resilient remote data integrity auditing schemes based on key update technique [16]. The data sharing is an important application in cloud storage scenarios. To protect the identity privacy of user, Wang et al. [17] designed a privacy-preserving shared data integrity auditing scheme by modifying the ring signature for secure cloud storage. Yang et al. [18] constructed an efficient shared data integrity auditing scheme, which not only supports the identity privacy but only achieves the identity traceability of users. Fu et al. [19] designed a privacy-aware shared data integrity auditing scheme by exploiting a homomorphic verifiable group signature. In order to support efficient user revocation, Wang et al. [20] proposed a shared data integrity auditing scheme with user revocation by using the proxy re-signature. With the employment of the Shamir secret sharing technique, Luo et al. [21] constructed a shared data integrity auditing scheme supporting user revocation. The aforementioned schemes all rely on Public Key Infrastructure (PKI), which incurs the considerable overheads from the complicated certificate management. To simplify certificate management, Wang [22] proposed an identity-based remote data integrity auditing scheme in multicloud storage. This scheme used the user’s identity information such as user’s name or e-mail address to replace the public key. Wang et al. [23] designed a novel identity-based proxyoriented remote data integrity auditing scheme by introducing a proxy to process data for users. Yu et al. [24] constructed a remote data integrity auditing scheme with perfect data privacy preserving in identity-based cryptosystems. Wang et al. [25] proposed an identity-based data integrity auditing scheme satisfying unconditional anonymity and incentive. Zhang et al. [26] proposed an identity-based remote data integrity auditing scheme for shared data supporting real efficient user revocation.
LATER¶6-10
III. LITERATURE SURVEY In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomor phic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in.To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation tech nique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. Using cloud storage, users can remotely store their data and enjoy the on-demand high-quality applications and services from a shared pool of configurable computing resources, without the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in cloud computing a formidable task, especially for users with constrained computing resources. Moreover, users should be able to just use the cloud storage as if it is local, without worrying about the need to verify its integrity. Thus, enabling public auditability for cloud storage is of critical importance so that users can resort to a third-party auditor (TPA) to check the integrity of outsourced data and be worry free. To securely introduce an effective TPA, the auditing process should bring in no new vulnerabilities toward user data privacy, and introduce no additional online burden to user. In this paper, we propose a secure cloud storage system supporting privacy-preserving public auditing. We further extend our result to enable the TPA to perform audits for multiple users simultaneously and efficiently. Extensive security and performance analysis show the proposed schemes are provably secure and highly efficient. Our preliminary experiment conducted on Amazon EC2 instance further demonstrates the fast performance of the design. To enable data sharing while concealing sensitive information, we adopt the concept of sanitizable signatures [10], whereby an authorized sanitizer is introduced to sanitize the sensitive portions of a file. However, directly applying this technique in remote data integrity auditing is impractical. First, the construction in relies on chameleon hashes, many of which suffer from key exposure vulnerabilities. To mitigate this issue, the scheme requires the use of strongly unforgeable chameleon hashes, which significantly increases computational costs [11]. Second, the signature scheme in lacks support for blockless verifiability, meaning that a verifier must retrieve the entire dataset from the cloud to check its integrity. This approach leads to excessive communication overhead and high verification latency, particularly in large-scale storage scenarios. Third, the scheme depends on a Public Key Infrastructure (PKI), which introduces the additional burden of complex certificate management.
EARLIER¶6-10
Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIFS.2018.2850312 the complicated certificate management. The security analysis and the performance evaluation show that the proposed scheme is secure and efficient. Index Terms—Cloud storage, data integrity auditing, data sharing, sensitive information hiding. I. INTRODUCTION W ITH the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud [1]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed [2]–[8]. In remote data integrity auditing schemes, the data owner firstly needs to generate signatures for data blocks before uploading them to the cloud. These signatures are used to prove the cloud truly possesses these data blocks in the phase of integrity auditing. And then the data owner uploads these data blocks along with their corresponding signatures to the cloud. The data stored in the cloud is often shared across multiple users in many cloud storage applications, such as Google Drive, Dropbox and iCloud. Data sharing as one of the most common features in cloud storage, allows a number of users to share their data with others. However, these shared data stored in the cloud might contain some sensitive information. For instance, the Electronic Health Records (EHRs) [9] stored and shared in the cloud usually contain patients’ sensitive information (patient’s name, telephone number and ID number, etc.) and the hospital’s sensitive information (hospital’s name, etc.). If these EHRs are directly uploaded to the cloud to be shared for research purposes, the sensitive information of patient and hospital will be inevitably exposed to the cloud and the researchers. Besides, the integrity of the EHRs needs to be guaranteed due to the existence of human errors and software/hardware failures in the cloud. Therefore, it is important to accomplish remote data integrity auditing on the condition that the sensitive information of shared data is protected. 1556-6013 © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
LATER¶15-19
containing the private information in EMR, and transform these blocks’ authenticators into the authenticators of sanitized EMR. The authenticators are utilized to check the data integrity. Using the above method, the EMR stored in the cloud can be shared with researchers while ensuring the privacy of private information and the integrity of EMR. In addition, our scheme can achieve block-level deduplication, in which only one copy of the deduplicated blocks in EMR needs to be stored. The conducted security analysis and performance evaluation affirm the security and efficiency of the proposed scheme. A. EXISTING SYSTEM With the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud, used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed. 1.Scalability Issues: The existing system may struggle to handle large-scale data storage and sharing requirements. As more users and data are added to the system, the computational and storage overhead for identity-based integrity auditing and sensitive information hiding can become a bottleneck, leading to performance degradation. 2.Complexity and Overhead: Implementing identity-based integrity auditing and sensitive information hiding typically involves complex cryptographic operations and additional metadata management. This can introduce overhead in terms of processing power and storage, potentially slowing down data access and sharing operations. 3.Key Management Challenges: Managing cryptographic keys for identity-based integrity auditing and data sharing can be challenging. If not handled properly, it can lead to key exposure risks or difficulties in key revocation and rotation. The existing system may not provide an efficient and userfriendly key management mechanism, making it less practical for users. B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users
EARLIER¶19-23
B. Related Work In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomorphic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in [5]. To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation technique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. To reduce the damage of users’ key exposure, Yu et al. [13] and [14], and Yu and Wang [15] proposed key-exposure resilient remote data integrity auditing schemes based on key update technique [16]. The data sharing is an important application in cloud storage scenarios. To protect the identity privacy of user, Wang et al. [17] designed a privacy-preserving shared data integrity auditing scheme by modifying the ring signature for secure cloud storage. Yang et al. [18] constructed an efficient shared data integrity auditing scheme, which not only supports the identity privacy but only achieves the identity traceability of users. Fu et al. [19] designed a privacy-aware shared data integrity auditing scheme by exploiting a homomorphic verifiable group signature. In order to support efficient user revocation, Wang et al. [20] proposed a shared data integrity auditing scheme with user revocation by using the proxy re-signature. With the employment of the Shamir secret sharing technique, Luo et al. [21] constructed a shared data integrity auditing scheme supporting user revocation. The aforementioned schemes all rely on Public Key Infrastructure (PKI), which incurs the considerable overheads from the complicated certificate management. To simplify certificate management, Wang [22] proposed an identity-based remote data integrity auditing scheme in multicloud storage. This scheme used the user’s identity information such as user’s name or e-mail address to replace the public key. Wang et al. [23] designed a novel identity-based proxyoriented remote data integrity auditing scheme by introducing a proxy to process data for users. Yu et al. [24] constructed a remote data integrity auditing scheme with perfect data privacy preserving in identity-based cryptosystems. Wang et al. [25] proposed an identity-based data integrity auditing scheme satisfying unconditional anonymity and incentive. Zhang et al. [26] proposed an identity-based remote data integrity auditing scheme for shared data supporting real efficient user revocation.
LATER¶15-19
containing the private information in EMR, and transform these blocks’ authenticators into the authenticators of sanitized EMR. The authenticators are utilized to check the data integrity. Using the above method, the EMR stored in the cloud can be shared with researchers while ensuring the privacy of private information and the integrity of EMR. In addition, our scheme can achieve block-level deduplication, in which only one copy of the deduplicated blocks in EMR needs to be stored. The conducted security analysis and performance evaluation affirm the security and efficiency of the proposed scheme. A. EXISTING SYSTEM With the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud, used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed. 1.Scalability Issues: The existing system may struggle to handle large-scale data storage and sharing requirements. As more users and data are added to the system, the computational and storage overhead for identity-based integrity auditing and sensitive information hiding can become a bottleneck, leading to performance degradation. 2.Complexity and Overhead: Implementing identity-based integrity auditing and sensitive information hiding typically involves complex cryptographic operations and additional metadata management. This can introduce overhead in terms of processing power and storage, potentially slowing down data access and sharing operations. 3.Key Management Challenges: Managing cryptographic keys for identity-based integrity auditing and data sharing can be challenging. If not handled properly, it can lead to key exposure risks or difficulties in key revocation and rotation. The existing system may not provide an efficient and userfriendly key management mechanism, making it less practical for users. B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users
EARLIER¶6-10
Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIFS.2018.2850312 the complicated certificate management. The security analysis and the performance evaluation show that the proposed scheme is secure and efficient. Index Terms—Cloud storage, data integrity auditing, data sharing, sensitive information hiding. I. INTRODUCTION W ITH the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud [1]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed [2]–[8]. In remote data integrity auditing schemes, the data owner firstly needs to generate signatures for data blocks before uploading them to the cloud. These signatures are used to prove the cloud truly possesses these data blocks in the phase of integrity auditing. And then the data owner uploads these data blocks along with their corresponding signatures to the cloud. The data stored in the cloud is often shared across multiple users in many cloud storage applications, such as Google Drive, Dropbox and iCloud. Data sharing as one of the most common features in cloud storage, allows a number of users to share their data with others. However, these shared data stored in the cloud might contain some sensitive information. For instance, the Electronic Health Records (EHRs) [9] stored and shared in the cloud usually contain patients’ sensitive information (patient’s name, telephone number and ID number, etc.) and the hospital’s sensitive information (hospital’s name, etc.). If these EHRs are directly uploaded to the cloud to be shared for research purposes, the sensitive information of patient and hospital will be inevitably exposed to the cloud and the researchers. Besides, the integrity of the EHRs needs to be guaranteed due to the existence of human errors and software/hardware failures in the cloud. Therefore, it is important to accomplish remote data integrity auditing on the condition that the sensitive information of shared data is protected. 1556-6013 © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
LATER¶15-19
containing the private information in EMR, and transform these blocks’ authenticators into the authenticators of sanitized EMR. The authenticators are utilized to check the data integrity. Using the above method, the EMR stored in the cloud can be shared with researchers while ensuring the privacy of private information and the integrity of EMR. In addition, our scheme can achieve block-level deduplication, in which only one copy of the deduplicated blocks in EMR needs to be stored. The conducted security analysis and performance evaluation affirm the security and efficiency of the proposed scheme. A. EXISTING SYSTEM With the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud, used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed. 1.Scalability Issues: The existing system may struggle to handle large-scale data storage and sharing requirements. As more users and data are added to the system, the computational and storage overhead for identity-based integrity auditing and sensitive information hiding can become a bottleneck, leading to performance degradation. 2.Complexity and Overhead: Implementing identity-based integrity auditing and sensitive information hiding typically involves complex cryptographic operations and additional metadata management. This can introduce overhead in terms of processing power and storage, potentially slowing down data access and sharing operations. 3.Key Management Challenges: Managing cryptographic keys for identity-based integrity auditing and data sharing can be challenging. If not handled properly, it can lead to key exposure risks or difficulties in key revocation and rotation. The existing system may not provide an efficient and userfriendly key management mechanism, making it less practical for users. B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users
EARLIER¶17-21
SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 333 Generally, these data blocks are replaced with wildcards. Furthermore, the sanitizer can transform these data blocks’ signatures into valid ones for the sanitized EHR. It makes the remote data integrity auditing still able to be effectively performed. During the process of sanitization, the sanitizer does not need to interact with medical doctors. Finally, the sanitizer uploads these sanitized EHRs and their corresponding signatures to the cloud. In this way, the EHRs can be shared and used by researchers, while the sensitive information of EHRs can be hidden. Meanwhile, the integrity of these EHRs stored in the cloud can be ensured. The sanitizer is necessary because of the following reasons. Firstly, after the data blocks corresponding to the patient’s sensitive information are blinded, the contents of these data blocks might become messy code. The sanitizer can unify the format by using wildcards to replace the contents of these data blocks. In addition, the sanitizer also can sanitize the data blocks corresponding to the hospital’s sensitive information such as hospital’s name by using wildcards, which protects the privacy of the hospital. Secondly, the sanitizer can facilitate the information management. It can sanitize the EHRs in bulk, and uploads these sanitized EHRs to the cloud at a fixed time. Thirdly, when the medical doctor needs the EHR, the sanitizer as the administrator of EHR information system can download the blinded EHR from the EHR information system and sends it to the medical doctor. The medical doctor can recover the original EHR from the blinded one. B. Related Work In order to verify the integrity of the data stored in the cloud, many remote data integrity auditing schemes have been proposed. To reduce the computation burden on the user side, a Third Party Auditor (TPA) is introduced to periodically verify the integrity of the cloud data on behalf of user. Ateniese et al. [2] firstly proposed a notion of Provable Data Possession (PDP) to ensure the data possession on the untrusted cloud. In their proposed scheme, homomorphic authenticators and random sampling strategies are used to achieve blockless verification and reduce I/O costs. Juels and Kaliski [3] defined a model named as Proof of Retrievability (PoR) and proposed a practical scheme. In this scheme, the data stored in the cloud can be retrieved and the integrity of these data can be ensured. Based on pseudorandom function and BLS signature, Shacham and Waters [4] proposed a private remote data integrity auditing scheme and a public remote data integrity auditing scheme. In order to protect the data privacy, Wang et al. [5] proposed a privacy-preserving remote data integrity auditing scheme with the employment of a random masking technique. Worku et al. [6] utilized a different random masking technique to further construct a remote data integrity auditing scheme supporting data privacy protection. This scheme achieves better efficiency compared with the scheme in [5]. To reduce the computation burden of signature generation on the user side, Guan et al. [7] designed a remote data integrity auditing scheme based on the indistinguishability obfuscation technique. Shen et al. [8] introduced a Third Party Medium (TPM) to design a light-weight remote data integrity auditing scheme. In this scheme, the TPM helps user generate signatures on the condition that data privacy can be protected. In order to support data dynamics, Ateniese et al. [10] firstly proposed a partially dynamic PDP scheme. Erway et al. [11] used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12] proposed another remote data integrity auditing scheme supporting full data dynamics by utilizing Merkle Hash Tree. To reduce the damage of users’ key exposure, Yu et al. [13] and [14], and Yu and Wang [15] proposed key-exposure resilient remote data integrity auditing schemes based on key update technique [16].
LATER¶15-19
containing the private information in EMR, and transform these blocks’ authenticators into the authenticators of sanitized EMR. The authenticators are utilized to check the data integrity. Using the above method, the EMR stored in the cloud can be shared with researchers while ensuring the privacy of private information and the integrity of EMR. In addition, our scheme can achieve block-level deduplication, in which only one copy of the deduplicated blocks in EMR needs to be stored. The conducted security analysis and performance evaluation affirm the security and efficiency of the proposed scheme. A. EXISTING SYSTEM With the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud, used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed. 1.Scalability Issues: The existing system may struggle to handle large-scale data storage and sharing requirements. As more users and data are added to the system, the computational and storage overhead for identity-based integrity auditing and sensitive information hiding can become a bottleneck, leading to performance degradation. 2.Complexity and Overhead: Implementing identity-based integrity auditing and sensitive information hiding typically involves complex cryptographic operations and additional metadata management. This can introduce overhead in terms of processing power and storage, potentially slowing down data access and sharing operations. 3.Key Management Challenges: Managing cryptographic keys for identity-based integrity auditing and data sharing can be challenging. If not handled properly, it can lead to key exposure risks or difficulties in key revocation and rotation. The existing system may not provide an efficient and userfriendly key management mechanism, making it less practical for users. B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users
EARLIER¶30-34
p, given g, gx and gy as input, output gxy ∈G1. The CDH assumption in G1 holds if it is computationally infeasible to solve the CDH problem in G1. 3) Discrete Logarithm (DL) Problem For unknown x ∈Z∗ p, given g and gx as input, outputs x. The DL assumption in G1 holds if it is computationally infeasible to solve the DL problem in G1. III. SYSTEM MODEL AND SECURITY MODEL A. System Model The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third Party Auditor (TPA), as shown in Fig.2. SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 335 (1) Cloud: The cloud provides enormous data storage space to the user. Through the cloud storage service, users can upload their data to the cloud and share their data with others. (2) User: The user is a member of an organization, which has a large number of files to be stored in the cloud. (3) Sanitizer: The sanitizer is in charge of sanitizing the data blocks corresponding to the sensitive information (personal sensitive information and the organization’s sensitive information) in the file, transforming these data blocks’ signatures into valid ones for the sanitized file, and uploading the sanitized file and its corresponding signatures to the cloud.
LATER¶16-20
containing the private information in EMR, and transform these blocks’ authenticators into the authenticators of sanitized EMR. The authenticators are utilized to check the data integrity. Using the above method, the EMR stored in the cloud can be shared with researchers while ensuring the privacy of private information and the integrity of EMR. In addition, our scheme can achieve block-level deduplication, in which only one copy of the deduplicated blocks in EMR needs to be stored. The conducted security analysis and performance evaluation affirm the security and efficiency of the proposed scheme. A. EXISTING SYSTEM With the explosive growth of data, it is a heavy burden for users to store the sheer amount of data locally. Therefore, more and more organizations and individuals would like to store their data in the cloud. However, the data stored in the cloud might be corrupted or lost due to the inevitable software bugs, hardware faults and human errors in the cloud, used a skip list to construct a fully data dynamic auditing scheme. Wang et al. [12]. In order to verify whether the data is stored correctly in the cloud, many remote data integrity auditing schemes have been proposed. 1.Scalability Issues: The existing system may struggle to handle large-scale data storage and sharing requirements. As more users and data are added to the system, the computational and storage overhead for identity-based integrity auditing and sensitive information hiding can become a bottleneck, leading to performance degradation. 2.Complexity and Overhead: Implementing identity-based integrity auditing and sensitive information hiding typically involves complex cryptographic operations and additional metadata management. This can introduce overhead in terms of processing power and storage, potentially slowing down data access and sharing operations. 3.Key Management Challenges: Managing cryptographic keys for identity-based integrity auditing and data sharing can be challenging. If not handled properly, it can lead to key exposure risks or difficulties in key revocation and rotation. The existing system may not provide an efficient and userfriendly key management mechanism, making it less practical for users. B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users V. CONCLUSION we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency to enhance the security and integrity of data stored in cloud environments. This project integrates identity-based auditing, which ensures that only authorized users can access and audit data, thereby maintaining privacy and traceability among group members.
EARLIER¶151-154
Fig. 8. The computation overhead in the process of signature generation and signature verification. Fig. 9. The computation overhead of the TPA in the phase of integrity auditing. Fig. 10. The computation overhead of the cloud in the phase of integrity auditing. 2) Performance of Auditing: With the different number of challenged data blocks, we respectively show the computation overhead of the TPA and that of the cloud in integrity auditing phase in Fig. 9 and Fig. 10. In our experiment, the number of challenged data blocks varies from 0 to 1,000. As shown in Fig. 9, we see the that the computation overheads of challenge generation and proof verification on the TPA side linearly increase with the number of challenged data blocks. The computation overhead of proof verification varies from 0.317s to 11.505s. Compared with the time of proof verification, the time of challenge generation increases slowly, just varying from 0.013s to 0461s. From Fig. 10, we have the observation that the computation overhead of proof generation on the cloud side varies from 0.021s to 3.981s. So we can conclude that, with the more challenged data blocks, both the TPA and the cloud will spend the more computation overheads. VII. CONCLUSION In this paper, we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 345 data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency.
LATER¶18-22
B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users V. CONCLUSION we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency to enhance the security and integrity of data stored in cloud environments. This project integrates identity-based auditing, which ensures that only authorized users can access and audit data, thereby maintaining privacy and traceability among group members. Additionally, the project addresses the challenge of sharing 478 files containing sensitive information by proposing methods to hide this sensitive data while still allowing the file to be shared and used by others. By doing so, it ensures that data integrity can be verified without exposing confidential information. Furthermore, the project explores the use of third-party auditors (TPAs) to independently verify the integrity of data stored in cloud storage, thereby providing an additional layer of security. The proposed solutions aim to balance the need for secure data sharing with the necessity of maintaining data integrity and confidentiality, making cloud storage a more secure and reliable option for users.
EARLIER¶152-154
Fig. 10. The computation overhead of the cloud in the phase of integrity auditing. 2) Performance of Auditing: With the different number of challenged data blocks, we respectively show the computation overhead of the TPA and that of the cloud in integrity auditing phase in Fig. 9 and Fig. 10. In our experiment, the number of challenged data blocks varies from 0 to 1,000. As shown in Fig. 9, we see the that the computation overheads of challenge generation and proof verification on the TPA side linearly increase with the number of challenged data blocks. The computation overhead of proof verification varies from 0.317s to 11.505s. Compared with the time of proof verification, the time of challenge generation increases slowly, just varying from 0.013s to 0461s. From Fig. 10, we have the observation that the computation overhead of proof generation on the cloud side varies from 0.021s to 3.981s. So we can conclude that, with the more challenged data blocks, both the TPA and the cloud will spend the more computation overheads. VII. CONCLUSION In this paper, we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports SHEN et al.: ENABLING IDENTITY-BASED INTEGRITY AUDITING AND DATA SHARING 345 data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency.
LATER¶18-22
B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users V. CONCLUSION we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency to enhance the security and integrity of data stored in cloud environments. This project integrates identity-based auditing, which ensures that only authorized users can access and audit data, thereby maintaining privacy and traceability among group members. Additionally, the project addresses the challenge of sharing 478 files containing sensitive information by proposing methods to hide this sensitive data while still allowing the file to be shared and used by others. By doing so, it ensures that data integrity can be verified without exposing confidential information. Furthermore, the project explores the use of third-party auditors (TPAs) to independently verify the integrity of data stored in cloud storage, thereby providing an additional layer of security. The proposed solutions aim to balance the need for secure data sharing with the necessity of maintaining data integrity and confidentiality, making cloud storage a more secure and reliable option for users.
EARLIER¶0-3
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 14, NO. 2, FEBRUARY 2019 331 Enabling Identity-Based Integrity Auditing and Data Sharing With Sensitive Information Hiding for Secure Cloud Storage Wenting Shen, Jing Qin, Jia Yu , Rong Hao, and Jiankun Hu , Senior Member, IEEE Abstract—With cloud storage services, users can remotely store their data to the cloud and realize the data sharing with others. Remote data integrity auditing is proposed to guarantee the integrity of the data stored in the cloud. In some common cloud storage systems such as the electronic health records system, the cloud file might contain some sensitive information. The sensitive information should not be exposed to others when the cloud file is shared. Encrypting the whole shared file can realize the sensitive information hiding, but will make this shared file unable to be used by others. How to realize data sharing with sensitive information hiding in remote data integrity auditing still has not been explored up to now. In order to address this problem, we propose a remote data integrity auditing scheme that realizes data sharing with sensitive information hiding in this paper. In this scheme, a sanitizer is used to sanitize the data blocks corresponding to the sensitive information of the file and transforms these data blocks’ signatures into valid ones for the sanitized file. These signatures are used to verify the integrity of the sanitized file in the phase of integrity auditing. As a result, our scheme makes the file stored in the cloud able to be shared and used by others on the condition that the sensitive information is hidden, while the remote data integrity auditing is still able to be efficiently executed. Meanwhile, the proposed scheme is based on identity-based cryptography, which simplifies Manuscript received February 13, 2018; revised May 10, 2018; accepted June 11, 2018. Date of publication June 25, 2018; date of current version August 2, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 61772311, Grant 61572267, and Grant 61272091, in part by the National Cryptography Development Fund of China under Grant MMJJ20170118, in part by the Open Project of Co-Innovation Center for Information Supply & Assurance Technology, Anhui University, and in part by the Open Project of the State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences under Grant 2017-MS-21 and Grant 2017-MS-05. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Ivan Visconti. (Corresponding author: Jing Qin.) W. Shen is with the School of Mathematics, Shandong University, Shandong 250100, China (e-mail: shenwentingmath@163.com). J. Qin is with the School of Mathematics, Shandong University, Shandong 250100, China, and also with the State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China (e-mail: qinjing@sdu.edu.cn).
LATER¶18-22
B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users V. CONCLUSION we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency to enhance the security and integrity of data stored in cloud environments. This project integrates identity-based auditing, which ensures that only authorized users can access and audit data, thereby maintaining privacy and traceability among group members. Additionally, the project addresses the challenge of sharing 478 files containing sensitive information by proposing methods to hide this sensitive data while still allowing the file to be shared and used by others. By doing so, it ensures that data integrity can be verified without exposing confidential information. Furthermore, the project explores the use of third-party auditors (TPAs) to independently verify the integrity of data stored in cloud storage, thereby providing an additional layer of security. The proposed solutions aim to balance the need for secure data sharing with the necessity of maintaining data integrity and confidentiality, making cloud storage a more secure and reliable option for users.
EARLIER¶10-14
1556-6013 © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 332 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 14, NO. 2, FEBRUARY 2019 this encrypted file, finally upload this encrypted file and its corresponding signatures to the cloud. This method can realize the sensitive information hiding since only the data owner can decrypt this file. However, it will make the whole shared file unable to be used by others. For example, encrypting the EHRs of infectious disease patients can protect the privacy of patient and hospital, but these encrypted EHRs cannot be effectively utilized by researchers any more. Distributing the decryption key to the researchers seems to be a possible solution to the above problem. However, it is infeasible to adopt this method in real scenarios due to the following reasons. Firstly, distributing decryption key needs secure channels, which is hard to be satisfied in some instances. Furthermore, it seems very difficult for a user to know which researchers will use his/her EHRs in the near future when he/she uploads the EHRs to the cloud. As a result, it is impractical to hide sensitive information by encrypting the whole shared file. Thus, how to realize data sharing with sensitive information hiding in remote data integrity auditing is very important and valuable. Unfortunately, this problem has remained unexplored in previous researches. Contribution The contribution of this paper can be summarized as follows: (1) We investigate how to achieve data sharing with sensitive information hiding in remote data integrity auditing, and propose a new concept called identity-based shared data integrity auditing with sensitive information hiding for secure cloud storage. In such a scheme, the sensitive information can be protected and the other information can be published. It makes the file stored in the cloud able to be shared and used by others on the condition that the sensitive information is protected, while the remote data integrity auditing is still able to be efficiently executed. (2) We design a practical identity-based shared data integrity auditing scheme with sensitive information hiding for secure cloud storage. A sanitizer is used to sanitize the data blocks corresponding to the sensitive information of the file. In our detailed scheme, firstly, the user blinds the data blocks corresponding to the personal sensitive information of the original file and generates the corresponding signatures, and then sends them to a sanitizer. The sanitizer sanitizes these blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information. It also transforms the corresponding signatures into valid ones for the sanitized file. This method not only realizes the remote data integrity auditing, but also supports the data sharing on the condition that sensitive information is protected in cloud storage. To the best of our knowledge, this is the first scheme with the above functions. Besides, our scheme is based on identity-based cryptography, which simplifies the complex certificate management. (3) We give the security analysis of the proposed scheme, and also justify the performance by concrete implementations. The result shows that the proposed scheme achieves desirable security and efficiency.
LATER¶18-22
B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users V. CONCLUSION we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency to enhance the security and integrity of data stored in cloud environments. This project integrates identity-based auditing, which ensures that only authorized users can access and audit data, thereby maintaining privacy and traceability among group members. Additionally, the project addresses the challenge of sharing 478 files containing sensitive information by proposing methods to hide this sensitive data while still allowing the file to be shared and used by others. By doing so, it ensures that data integrity can be verified without exposing confidential information. Furthermore, the project explores the use of third-party auditors (TPAs) to independently verify the integrity of data stored in cloud storage, thereby providing an additional layer of security. The proposed solutions aim to balance the need for secure data sharing with the necessity of maintaining data integrity and confidentiality, making cloud storage a more secure and reliable option for users.
EARLIER¶0-3
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 14, NO. 2, FEBRUARY 2019 331 Enabling Identity-Based Integrity Auditing and Data Sharing With Sensitive Information Hiding for Secure Cloud Storage Wenting Shen, Jing Qin, Jia Yu , Rong Hao, and Jiankun Hu , Senior Member, IEEE Abstract—With cloud storage services, users can remotely store their data to the cloud and realize the data sharing with others. Remote data integrity auditing is proposed to guarantee the integrity of the data stored in the cloud. In some common cloud storage systems such as the electronic health records system, the cloud file might contain some sensitive information. The sensitive information should not be exposed to others when the cloud file is shared. Encrypting the whole shared file can realize the sensitive information hiding, but will make this shared file unable to be used by others. How to realize data sharing with sensitive information hiding in remote data integrity auditing still has not been explored up to now. In order to address this problem, we propose a remote data integrity auditing scheme that realizes data sharing with sensitive information hiding in this paper. In this scheme, a sanitizer is used to sanitize the data blocks corresponding to the sensitive information of the file and transforms these data blocks’ signatures into valid ones for the sanitized file. These signatures are used to verify the integrity of the sanitized file in the phase of integrity auditing. As a result, our scheme makes the file stored in the cloud able to be shared and used by others on the condition that the sensitive information is hidden, while the remote data integrity auditing is still able to be efficiently executed. Meanwhile, the proposed scheme is based on identity-based cryptography, which simplifies Manuscript received February 13, 2018; revised May 10, 2018; accepted June 11, 2018. Date of publication June 25, 2018; date of current version August 2, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 61772311, Grant 61572267, and Grant 61272091, in part by the National Cryptography Development Fund of China under Grant MMJJ20170118, in part by the Open Project of Co-Innovation Center for Information Supply & Assurance Technology, Anhui University, and in part by the Open Project of the State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences under Grant 2017-MS-21 and Grant 2017-MS-05. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Ivan Visconti. (Corresponding author: Jing Qin.) W. Shen is with the School of Mathematics, Shandong University, Shandong 250100, China (e-mail: shenwentingmath@163.com). J. Qin is with the School of Mathematics, Shandong University, Shandong 250100, China, and also with the State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China (e-mail: qinjing@sdu.edu.cn).
LATER¶18-22
B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users V. CONCLUSION we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency to enhance the security and integrity of data stored in cloud environments. This project integrates identity-based auditing, which ensures that only authorized users can access and audit data, thereby maintaining privacy and traceability among group members. Additionally, the project addresses the challenge of sharing 478 files containing sensitive information by proposing methods to hide this sensitive data while still allowing the file to be shared and used by others. By doing so, it ensures that data integrity can be verified without exposing confidential information. Furthermore, the project explores the use of third-party auditors (TPAs) to independently verify the integrity of data stored in cloud storage, thereby providing an additional layer of security. The proposed solutions aim to balance the need for secure data sharing with the necessity of maintaining data integrity and confidentiality, making cloud storage a more secure and reliable option for users.
EARLIER¶10-14
1556-6013 © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 332 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 14, NO. 2, FEBRUARY 2019 this encrypted file, finally upload this encrypted file and its corresponding signatures to the cloud. This method can realize the sensitive information hiding since only the data owner can decrypt this file. However, it will make the whole shared file unable to be used by others. For example, encrypting the EHRs of infectious disease patients can protect the privacy of patient and hospital, but these encrypted EHRs cannot be effectively utilized by researchers any more. Distributing the decryption key to the researchers seems to be a possible solution to the above problem. However, it is infeasible to adopt this method in real scenarios due to the following reasons. Firstly, distributing decryption key needs secure channels, which is hard to be satisfied in some instances. Furthermore, it seems very difficult for a user to know which researchers will use his/her EHRs in the near future when he/she uploads the EHRs to the cloud. As a result, it is impractical to hide sensitive information by encrypting the whole shared file. Thus, how to realize data sharing with sensitive information hiding in remote data integrity auditing is very important and valuable. Unfortunately, this problem has remained unexplored in previous researches. Contribution The contribution of this paper can be summarized as follows: (1) We investigate how to achieve data sharing with sensitive information hiding in remote data integrity auditing, and propose a new concept called identity-based shared data integrity auditing with sensitive information hiding for secure cloud storage. In such a scheme, the sensitive information can be protected and the other information can be published. It makes the file stored in the cloud able to be shared and used by others on the condition that the sensitive information is protected, while the remote data integrity auditing is still able to be efficiently executed. (2) We design a practical identity-based shared data integrity auditing scheme with sensitive information hiding for secure cloud storage. A sanitizer is used to sanitize the data blocks corresponding to the sensitive information of the file. In our detailed scheme, firstly, the user blinds the data blocks corresponding to the personal sensitive information of the original file and generates the corresponding signatures, and then sends them to a sanitizer. The sanitizer sanitizes these blinded data blocks into a uniform format and also sanitizes the data blocks corresponding to the organization’s sensitive information. It also transforms the corresponding signatures into valid ones for the sanitized file. This method not only realizes the remote data integrity auditing, but also supports the data sharing on the condition that sensitive information is protected in cloud storage. To the best of our knowledge, this is the first scheme with the above functions. Besides, our scheme is based on identity-based cryptography, which simplifies the complex certificate management. (3) We give the security analysis of the proposed scheme, and also justify the performance by concrete implementations. The result shows that the proposed scheme achieves desirable security and efficiency.
LATER¶18-22
B. PROPOSED SYSTEM The system model involves five kinds of different entities: the cloud, the user, the sanitizer, the Private Key Generator (PKG) and the Third-Party Auditor (TPA), as shown in Fig 1. 1.Improved Usability: The proposed system may offer a more user-friendly interface and seamless integration with cloud storage services. 2.Enhanced Scalability: By optimizing resource usage and employing efficient cryptographic techniques, the proposed system can potentially offer better scalability. It may handle larger volumes of data and more users while maintaining acceptable performance levels, addressing one of the disadvantages of the existing system. 3.Robust Security: The proposed system could enhance security by implementing advanced encryption and access control mechanisms. It may also include robust key management solutions, reducing the risk of key exposure and ensuring the confidentiality and integrity of sensitive data. Figure 1: Architecture of the Proposed System IV.RESULTS Improving security in cloud storage involves several innovative approaches to ensure data integrity, privacy, and efficient sharing. Here are some key methods: Identity-Based Integrity Auditing: One approach is the use of Secure Identity-Based Aggregate Signatures (SIBAS) combined with Trusted Execution Environment (TEE) for data integrity verification. SIBAS allows for the checking of data integrity while TEE, running on local infrastructure, acts as an auditor to verify the outsourced data and manage keys securely. This method reduces the risk of key leakage and ensures that users' private information remains confidential. Hidden Data and Sensitive Information Protection: Another critical aspect is the protection of sensitive information within shared files. A proposed scheme enables data sharing while hiding sensitive information. This is achieved by selectively encrypting only the sensitive parts of the data, allowing the rest to remain accessible and usable by authorized users. This approach ensures that the integrity of the data is maintained without compromising privacy. Lightweight Secure Auditing: For shared data in cloud storage, a lightweight secure auditing scheme can be implemented. This scheme introduces a Third Party Auditor (TPA) to conduct integrity checks and verify shared data. The TPA ensures that the auditing process is efficient and does not impose additional burdens on users, thereby enhancing both security and usability These methods collectively enhance the security of cloud storage by addressing data integrity, privacy, and efficient sharing, making cloud services more reliable and trustworthy for users V. CONCLUSION we proposed an identity-based data integrity auditing scheme for secure cloud storage, which supports data sharing with sensitive information hiding. In our scheme, the file stored in the cloud can be shared and used by others on the condition that the sensitive information of the file is protected. Besides, the remote data integrity auditing is still able to be efficiently executed. The security proof and the experimental analysis demonstrate that the proposed scheme achieves desirable security and efficiency to enhance the security and integrity of data stored in cloud environments. This project integrates identity-based auditing, which ensures that only authorized users can access and audit data, thereby maintaining privacy and traceability among group members. Additionally, the project addresses the challenge of sharing 478 files containing sensitive information by proposing methods to hide this sensitive data while still allowing the file to be shared and used by others. By doing so, it ensures that data integrity can be verified without exposing confidential information. Furthermore, the project explores the use of third-party auditors (TPAs) to independently verify the integrity of data stored in cloud storage, thereby providing an additional layer of security. The proposed solutions aim to balance the need for secure data sharing with the necessity of maintaining data integrity and confidentiality, making cloud storage a more secure and reliable option for users.