Arbitrarily Fast Switched Distributed Stabilization of Partially Unknown Interconnected Multiagent Systems: A Proactive Cyber Defense Perspective

TL;DR

This paper introduces a proactive cyber defense framework for multiagent systems, enabling arbitrarily fast topology switching and enhanced resilience against cyber attacks through a combined control and cybersecurity design approach.

Contribution

It develops a mixed control and cybersecurity design framework allowing rapid topology switching and unpredictability to improve system resilience against cyber threats.

Findings

Proposes a step-by-step control design for arbitrarily fast switching.

Uses satisfiability modulo theory for security-aware topology design.

Validates robustness and security through simulations.

Abstract

A design framework recently has been developed to stabilize interconnected multiagent systems in a distributed manner, and systematically capture the architectural aspect of cyber-physical systems. Such a control theoretic framework, however, results in a stabilization protocol which is passive with respect to the cyber attacks and conservative regarding the guaranteed level of resiliency. We treat the control layer topology and stabilization gains as the degrees of freedom, and develop a mixed control and cybersecurity design framework to address the above concerns. From a control perspective, despite the agent layer modeling uncertainties and perturbations, we propose a new step-by-step procedure to design a set of control sublayers for an arbitrarily fast switching of the control layer topology. From a proactive cyber defense perspective, we propose a satisfiability modulo theory formulation to obtain a set of control sublayer structures with security considerations, and offer a frequent and fast mutation of these sublayers such that the control layer topology will remain unpredictable for the adversaries. We prove the robust input-to-state stability of the two-layer interconnected multiagent system, and validate the proposed ideas in simulation.