An Entropy-View Secure Multiparty Computation Protocol Based on Semi-Honest Model

Abstract

Data interaction scenarios involving multiple parties in network communities have problems of trust, data security, and reliability of the parties, and secure multiparty computation(SMPC) can effectively solve these problems. To address the security and fairness issues of SMPC, this study considers that semi-honest participants can lead to deviations in the security and fairness of the protocol, and combines information entropy and mutual information to present an n-round information exchange protocol in which each participant broadcasts a relevant information value in each round without revealing other information. The uncertainty of the correct outcome value is blurred by the interaction information in each round, and each participant is not sure of the correct outcome value until the end of the protocol, which effectively prevents malicious behavior and ensures the correct execution of the protocol. Security and fairness analysis shows that our protocol guarantees the security and relative fairness of the output obtained by the participants after completing the protocol.