Title

Blockchain-based public auditing and secure deduplication with fair arbitration

RIS ID

144495

Publication Details

Yuan, H., Chen, X., Wang, J., Yuan, J., Yan, H. & Susilo, W. (2020). Blockchain-based public auditing and secure deduplication with fair arbitration. Information Sciences, 541 409-425.

Abstract

© 2020 Elsevier Inc. Data auditing enables data owners to verify the integrity of their sensitive data stored at an untrusted cloud without retrieving them. This feature has been widely adopted by commercial cloud storage. However, the existing approaches still have some drawbacks. On the one hand, the existing schemes have a defect of fair arbitration, i.e., existing auditing schemes lack an effective method to punish the malicious cloud service provider (CSP) and compensate users whose data integrity is destroyed. On the other hand, a CSP may store redundant and repetitive data. These redundant data inevitably increase management overhead and computational cost during the whole data life cycle. To address these challenges, we propose a blockchain-based public auditing and secure deduplication scheme with fair arbitration. By using a smart contract, our scheme supports automatic penalization of the malicious CSP and compensates users whose data integrity is damaged. Moreover, our scheme introduces a message-locked encryption algorithm and removes the random masking in data auditing. Compared with the existing schemes, our scheme can effectively reduce the computational cost of tag verification and data storage costs. We give a comprehensive analysis to demonstrate the correctness of the proposed scheme in terms of storage, batch auditing, and data consistency. Also, extensive experiments conducted on the platform of Ethereum blockchain demonstrate the efficiency and effectiveness of our scheme.

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Link to publisher version (DOI)

http://dx.doi.org/10.1016/j.ins.2020.07.005