Blockchain-Based Data Integrity Verification
Zhijie Han, Xingbo Xie, Xiaoyu Du, Ying Du, Xin He · 2024
With the popularity of cloud storage, data integrity verification has become a challenging issue. Traditional centralized auditing techniques rely on third-party auditors (TPAs), who not only suffer from single points of failure and security vulnerabilities but are also not fully trustworthy. Blockchain technology offers a new approach to solving this problem. This paper proposes a data integrity verification framework based on blockchain. The scheme employs Merkle tree and Interval Tree structures by constructing an independent Merkle tree for each data fragment. The root hash values of these individual Merkle trees are subsequently aggregated to form an Interval Tree. Leveraging the tamper-proof features of the blockchain, the root hash summaries are uploaded to the blockchain for preservation. Additionally, we introduce a novel verification method based on Shamir's Secret Sharing (SSS), which effectively safeguards data privacy. Furthermore, the use of Merkle Tree and Interval Tree aims to optimize the retrieval process, enhancing the efficiency of data integrity verification. Finally, theoretical analysis and experimental results demonstrate that the scheme improves processing speed and reduces resource consumption.