Blockchain-Based Dynamic Cloud Data Integrity Auditing via Non-Leaf Node Sampling of Rank-Based Merkle Hash Tree

Cloud storage plays an important role in the era of Big Data and Web 3.0. More and more data owners (DOs) store their data on Cloud for convenience and affordability. However, security and integrity completely depend on cloud storage service providers (CSPs) after data outsourcing. Once CSPs commit dishonest actions that lead to data tampering or loss, it will cause huge losses to DOs. Therefore, DOs need to audit the integrity of their data regularly. Traditional auditing schemes rely on trusted third parties (TPAs), which are not always trustworthy. This paper utilizes Blockchain instead of a trusted third-party auditor for data integrity auditing to address the trust crisis between data owners and cloud storage providers. Existing Rank-based Merkle Hash Tree (RMHT)-based auditing approaches suffer from high communication cost, limiting its applications to Blockchain scenarios. To address these issues, we enhance the auditing algorithm through extending the Rank-based Merkle Hash Tree (RMHT) for dynamic update of stored data and using a non-leaf node sampling strategy. These modifications significantly reduce the communication overhead during auditing and update phases. Such optimizations enable the algorithm to be well-suited for the Blockchain environment because proofs are stored on the Blockchain with gas fees. We implement a prototype and perform a security analysis of the proposed system. Experimental results demonstrate the security and effectiveness of the proposed approach.