Defense strategies against network attacks in cyber-physical systems with analysis cost constraint based on honeypot game model

Abstract

Cyber-physical system (CPS) is an advanced system that integrats physical processes, computation and communication resources. The security of cyber-physical systems has become an active research area in recent years. In this paper, we focus on defensive strategies against network attacks in CPS. We introduce both low- and high-interaction honeypots into CPS as a security management tool deliberately designed to be probed, attacked and compromised. In addition, an analysis resource constraint is introduced for the purpose of optimizing defensive strategies against network attacks in CPS. We study the offensive and defensive interactions of CPS and model the offensive and defensive process as an incomplete information game with the assumption that the defender's analysis resource is unknown to the attacker. We prove the existence of several Bayesian-Nash equilibria in the low- and high-interaction honeypot game without analysis cost constraints and obtain the attacker's equilibrium strategy firstly. Then, we take the impact of analysis cost on the capture effect of honeypots into consideration and further optimize the defensive strategy by allocating analysis resource between low- and high-interaction honeypot with resource constraint. Finally, the proposed method is evaluated through numerical simulation and prove to be effective in obtaining the optimal defensive strategy.