Dynamic Proofs of Retrievability for Coded Cloud Storage Systems

Abstract

Cloud storage allows users to store their data in a remote server to get rid of expensive local storage and management costs and then access data of interest anytime anywhere. A number of solutions have been proposed to tackle the verification of remote data integrity and retrievability in cloud storage systems. Most of existing schemes, however, do not support efficient data dynamics and/or suffer from security vulnerabilities when involving dynamic data operations. In this paper, we propose a dynamic proof of retrievability scheme supporting public auditability and communication-efficient recovery from data corruptions. To this end, we split up the data into data blocks and encode each data block individually using outer code and inner code before outsourcing so that i) an update inside any data block only affects a few codeword symbols and ii) communication-efficient data repair for a breakdown server can be achieved and communication overhead for small data corruptions within a server can be eliminated. Based on the encoded data blocks, we utilize rb23Tree to enforce the data sequence for dynamic operations, preventing the cloud service provider from manipulating data block to pass the integrity check in the dynamic scenario. We also analyze the effectiveness of the proposed construction in defending against pollution attacks during data recovery. Formal security analysis and extensive experimental evaluations are conducted, showing that the proposed scheme is practical for use in cloud storage systems.

Dynamic Outsourced Proofs of Retrievability Enabling Auditing Migration for Remote Storage Security

“…However, at the side of the cloud storage server (CSS), there still exist all kinds of internal and external threats against the storage security of outsourced data, such as Byzantine failures, the monetary reasons, and the hacker attacks [5,6]. So, it is well known that CSS would be considered as a malicious entity that might try to hide the accident when data loss occurs, or even deliberately delete client's data for saving storage cost.…”

“…However, given the fact that most mobile clients only have a limited capacity so that these clients are unlikely to keep online all the time to perform the frequent auditing, various public auditing schemes are proposed [5,6,[9][10][11] for auditing migration, which enables mobile client to free herself by moving the heavy auditing tasks to a third-party auditor (TPA). But existing public schemes rely on the hypothesis 2 Wireless Communications and Mobile Computing that TPA is trusted to complete the migrated auditing tasks, meaning that these schemes do not provide any security guarantee to resist a malicious TPA that might break the auditing protocols, which is exactly the potential risk that has not been covered by current public auditing schemes [12].…”

“…Supporting dynamic updates is an essential requirement for numerous practical cloud storage applications [13]. Although all kinds of authenticated data structures [6,9,[13][14][15][16] have been proposed to support data dynamics, there still exist research gaps in these structures. For one thing, most existing dynamic authenticated data structures [9,[14][15][16] are designed based on the Merkle Hash Tree (MHT).…”

“…For example, the height of MHT will increase linearly when many new data blocks are continuously inserted in the same leaf position, so in this worst case the expected (log ) performance cannot be ensured for authenticating the index and value of any appointed leaf node via MHT. For another, although some other authenticated structures such as rb23Tree [6] and Skip List [13] are proposed for dynamism, when there is a need to verify multiple leaf nodes of different data blocks (i.e., authenticate the indices and values of these leaf nodes), all above-mentioned dynamic methods merely adopt the straightforward way of verifying these different leaf nodes one by one with their respective proof paths. Since the verification upon a single proof path is of (log ) bandwidth and computation costs, as the number of verified leaf nodes increases, it is clearly not an efficient way to separately verify that many leaf nodes one by one.…”

Data Compression Technique for Cloud Storage in Multi-User Environments

“…The above type of systems will not be appropriate for distributed storage environment administrations where clients can check the trustworthiness as often as possible, for example, consistently. Subsequently, scientists presented proof of the storage to check the uprightness without copying documents from cloud storage [5]. Besides, clients may likewise require a few element operations, for example, alteration, addition, and cancellation, to upgrade their documents, while keeping up the capacity PoS is proposed for such element updating.…”