Blockchain-assisted secure multi-party computation with verification and auditing

Lei Zhang, Yixin Jiang, Hongjian Yin, Yakun Niu, Lei Tan, Yinfeng Hao

Abstract: Under the rapid development of big data and cloud computing, emerging applications have seen significant improvements in efficiency and service quality. Nevertheless, the conflict between data sharing and privacy preservation remains a major obstacle to the advancement of big data technology. Addressing this issue, this study introduces a solution tailored to the big data environment, which achieves privacy protection and auditability in data sharing and processing. This approach separates data ownership, usage, and validation to mitigate privacy breaches and improper computing behaviors. Leveraging blockchain technology, a transparent governance platform is constructed to identify and track illegal data and computing activities. Furthermore, the solution integrates noninteractive zero-knowledge proofs for publicly verifying data consistency and computing validity on the blockchain. Experimental analysis on computational latency, communication costs, and encryption parameters confirms the feasibility and efficacy of this approach.