Towards Privacy Preserving Consensus Control in Multi-Agent Cyber-Physical Systems Subject to Cyber Attacks

Abstract

Multi-agent systems (MAS) require sharing their information with their neighboring agents to reach a consensus in a distributed manner. In this paper, a transformation-based consensus control methodology is developed and implemented that can be utilized to reach a consensus among agents in a distributed manner without revealing their true information to their neighboring agents. The proposed methodology protects agents privacy against eavesdropper adversaries and malicious agents capable of intercepting and accessing the agents' exchanged data. A unique isometric isomorphism is employed for each agent to map the true value of exchanged sensor measurements and state estimates. By leveraging the property of isometric isomorphism in preserving norms, it is shown that reaching a consensus among agents is equivalent to that can be accomplished by the transformed agents dynamics. Numerical case studies are provided to illustrate the effectiveness of the proposed and developed methodology in preserving agents' privacy while ensuring that the MAS accomplish consensus requirements despite the presence of cyber attacks.