A Scheme of Robust Privacy-Preserving Multi-Party Computation via Public Verification

【Author】 Gai, Keke; Wang, Dongjue; Yu, Jing; Zhu, Liehuang; Meng, Weizhi

【Source】IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING

【影响因子】6.791

【Abstract】Multi-Party Computation (MPC), as a distributed computing paradigm, is considered to be a potential solution for providing privacy-preserving for applications following the client-server model. However, traditional MPC solutions cannot satisfy the publicly verifiable requirement of the client-server model. In this paper, we propose a blockchain-based verifiable MPC solution using Pedersen's threshold secret sharing and Lifted ElGamal encryption. We first build a data distribution method using Pedersen's threshold secret sharing and symmetric encryption to protect the privacy of inputs while ensuring robustness. Then, we propose a result processing algorithm using Lifted ElGamal encryption to safeguard the privacy of the outputs. Finally, we employ non-interactive zero-knowledge proof and Pedersen commitment to publicly verify the correctness of the encrypted outputs in the smart contract, enabling the detection of malicious parties. Theoretical analysis indicates that the proposed method can publicly verify the correctness of outputs without revealing plain-text inputs and outputs, which satisfy the privacy-preserving requirements of the client-server model. Experimental evaluations have demonstrated that our proposed approach is efficient regarding computation overhead, communication overhead, and response time in the output verification phase while achieving stronger privacy and robustness.

【Keywords】Servers; Cryptography; Privacy; Blockchains; Data privacy; Homomorphic encryption; Additives; Smart contracts; Robustness; Multi-party computation; blockchain; public verification; robustness; privacy-preserving

【发表时间】2025 SEP

【收录时间】2025-09-11

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