Privacy-Preserving Bipartite Consensus on Signed Networks

This paper addresses the privacy-preserving bipartite consensus problem on signed networks. Traditional bipartite consensus protocols need agents to explicitly exchange initial state with their neighbors, which is undesirable when the state is private or contains some sensitive information. Therefore, in this paper, a privacy-preserving bipartite consensus algorithm is proposed, and it aims to compute the accurate bipartite consensus value while preserving the initial state information of agents. The core idea of this algorithm is to exchange encrypted random values between cooperative agents before information iterative update, and then agent constructs false initial states based on these random values to replace the original initial states for transmission. A specific correctness analysis and privacy analysis are given subsequently. Finally, numerical examples are given to show the effectiveness of this algorithm and its superiority over some existing methods.