Dynamic Provable Data Possession Scheme Research Articles

Improved Outsourced Provable Data Possession for Secure Cloud Storage

With the advent of data outsourcing, how to efficiently verify the integrity of data stored at an untrusted cloud service provider (CSP) has become a significant problem in cloud storage. In 2019, Guo et al. proposed an outsourced dynamic provable data possession scheme with batch update for secure cloud storage. Although their scheme is very novel, we find that their proposal is not secure in this paper. The malicious cloud server has ability to forge the authentication labels, and thus it can forge or delete the user’s data but still provide a correct data possession proof. Based on the original protocol, we proposed an improved one for the auditing scheme, and our new protocol is effective yet resistant to attacks.

Stern–Brocot-Based Non-Repudiation Dynamic Provable Data Possession

With the widespread popularity of cloud storage, cloud storage security issues have also received much attention. A provable data possession (PDP) scheme can effectively help users to verify the integrity of data stored remotely in the cloud. For this reason, the client’s PDP scheme is constantly improving and developing. A non-repudiable dynamic PDP scheme based on the Stern–Brocot tree (Stern–Brocot-based non-repudiation dynamic provable data possession, abbreviated as SB-NR-DPDP) is proposed in view of the problem that the existing PDP scheme pays less attention to the clients deceiving the cloud server. We put forward a dynamic storage structure and dynamic operation algorithm based on the Stern–Brocot tree so that it can satisfy the client’s dynamic data operations and realize the non-repudiation feature of the scheme. This scheme provides tag-unforgeability and proof-unforgeability against adaptive chosen-message attacks. The scheme can also resist hash value attacks, delete–insert attacks, and tamper with cloud return value attacks. The theoretical analysis shows that the proposed scheme has less computing overhead and storage overhead. As such, it has better safety and efficiency than other schemes.

Identity-based non-repudiable dynamic provable data possession in cloud storage

In cloud-assisted wearable devices, how to protect the integrity of data stored in the cloud is a hot issue. For the scenes where clients are dishonest, we study the non-repudiable dynamic provable data possession schemes, and find that existing dynamic structures are not suitable for non-repudiable dynamic provable data possession schemes. The Merkle hash tree must be combined with timestamps to construct non-repudiable dynamic provable data possession schemes. This will cause the synchronization problem, and map-version tables cannot resist delete-insert attacks. Therefore, we propose a monotonic dynamic structure, i.e., index logic table. Then, we construct an identity based non-repudiable dynamic provable data possession scheme for cloud storage by using index logic tables. The proposed scheme not only resists the hash value stored attack, the delete-insert attack, and the tampering cloud returned value attack, but also avoids the synchronization problem. Furthermore, the proposed scheme has lower computation cost and storage cost in the dynamic operation process.

Optimized algorithms for flexible length-based authenticated skip list

With the growing trend toward using cloud storage, the problem of efficiently checking and proving data integrity needs more consideration. Many cryptography and security schemes, such as PDP (Provable Data Possession) and POR (Proofs of Retrievability) were proposed for this problem. Although many efficient schemes for static data have been constructed, only a few dynamic schemes exist, such as DPDP (Dynamic Provable Data Possession). But the DPDP scheme falls short when updates are not proportional to a fixed block size. The FlexList-based Dynamic Provable Data Possession (FlexDPDP) was an optimized scheme for DPDP. However, the update operations (insertion, remove, modification) in Flex DPDP scheme only apply to single node at a time, while multiple consecutive nodes operation is more common in practice. To solve this problem, we propose optimized algorithms for multiple consecutive nodes, which including MultiNodes Insert and Verification, MultiNodes Remove and Verification, MultiNodes Modify and Verification. The cost of our optimized algorithms is also analyzed. For m consecutive nodes, an insertion takes O(m) + O(log N) + O(log m), where N is the number of leaf nodes of FlexList, a remove takes O(log N), and a modification is the same as the original algorithm. Finally, we compare the optimized algorithms with original Flex-List through experiences, and the results show that our scheme has the higher efficiency of time and space.

Dynamic Provable Data Possession

As storage-outsourcing services and resource-sharing networks have become popular, the problem of efficiently proving the integrity of data stored at untrusted servers has received increased attention. In the Provable Data Possession (PDP) model, the client preprocesses the data and then sends them to an untrusted server for storage while keeping a small amount of meta-data. The client later asks the server to prove that the stored data have not been tampered with or deleted (without downloading the actual data). However, existing PDP schemes apply only to static (or append-only) files. We present a definitional framework and efficient constructions for Dynamic Provable Data Possession (DPDP), which extends the PDP model to support provable updates to stored data. We use a new version of authenticated dictionaries based on rank information. The price of dynamic updates is a performance change from O (1) to O (log n (or O ( n ε log n )) for a file consisting of n blocks while maintaining the same (or better, respectively) probability of misbehavior detection. Our experiments show that this slowdown is very low in practice (e.g., 415KB proof size and 30ms computational overhead for a 1GB file). We also show how to apply our DPDP scheme to outsourced file systems and version control systems (e.g., CVS).

Improved fair and dynamic provable data possession supporting public verification

A number of proposals have been suggested to tackle data integrity and privacy concerns in cloud storage in which some existing schemes suffer from vulnerabilities in data dynamics. In this paper, we propose an improved fairness and dynamic provable data possession scheme that supports public verification and batch auditing while preserves data privacy. The rb23Tree is utilized to facilitate data dynamics. Moreover, the fairness is considered to prevent a dishonest user from accusing the cloud service provider of manipulating the data. The scheme allows a third party auditor (TPA) to verify the data integrity without learning any information about the data content during the auditing process. Furthermore, our scheme also allows batch auditing, which greatly accelerates the auditing process when there are multiple auditing requests. Security analysis and extensive experimental evaluations show that our scheme is secure and efficient.