Journal
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
Volume 131, Issue -, Pages 183-193Publisher
ELSEVIER
DOI: 10.1016/j.future.2022.01.019
Keywords
Cloud storage; Integrity verification; Random auditor committee; Election algorithm; Blockchain
Categories
Funding
- National Natural Science Foundation ofChina [62072105, 61872087]
- NaturalScience Foundation of Fujian Province, China
- Center-initiated Research Project of Zhejiang Lab, China
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This study proposes a blockchain-based random auditor committee (BRAC) scheme for integrity verification of outsourced data. The scheme utilizes a verifiable random function to select a third-party auditor committee for contract verification, and improves security through the randomness of leader election.
With the popularity of cloud storage, integrity verification for outsourced data has attracted more and more attention. The majority of existing research works rely on a unique third-party auditor (TPA) or fixed TPAs to audit the integrity of outsourced data, and thus they are vulnerable to DoS and collusion attacks as the TPA is not completely trusted. To conquer this problem, a blockchain-based random auditor committee is proposed to replace the fixed TPAs for the integrity verification (call BRAC scheme for short). The proposed blockchain consensus algorithm utilizes a verifiable random function (VRF) to select the third-party auditor committee (TPAC) which performs contract verification. The leader of TPAs (LTPA) packs the verification proof into a blockchain called verification chain. The main idea is employing the output of a VRF for leader election to make it probabilistic, such that specific nodes cannot be targeted in advance and a certain fraction of the nodes being malicious can be tolerated. We present rigorous security analysis to demonstrate the security of the proposed scheme. Meanwhile, the comprehensive performance evaluation shows that the proposed scheme improves the performance of data integrity verification effectively. (c) 2022 Elsevier B.V. All rights reserved.
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