Resilient Distributed Optimization Against Cyber-Attacks

Abstract

This paper presents a novel resilient distributed optimization algorithm for a network of agents. It guarantees that the local estimates of the agents converge close to the optimal solution of the original optimization problem, even in the presence of unknown but bounded attacks on both the agent’s local computation and communication network. To this end, a virtual state is introduced, which also enables each agent to identify the compromised communication links in real-time and in a distributed manner. The distributed algorithm imposes no restrictions on the maximum tolerable number of attacks, and it does not require high network connectivity and trusted/secured agents or edges. A numerical example is provided to illustrate the results.