Cyber-Physical Security Evaluation in Manufacturing Systems with a Bayesian Game Model

Abstract

Cyber-physical security has been taken more seriously recently in manufacturing systems because of highly increasing integration of cyber and network systems with physical production known as cyber-physical manufacturing systems (CPMS). This paper presents a novel proactive approach to forecast the interrelation of attackers and cyber-physical manufacturing systems to suggest a proper defense strategy to the system managerial. In this research, the zero-sum game payoff function developed in our previous studies is transformed into an epistemic type Bayesian game that addresses uncertainties on types of players. The risk preference behavior also is considered as a characteristic of different types of players and to form the Bayesian utility function. Finally, a numerical example is analyzed with a structured method by developing the Bayesian game, computing Bayes-Nash equilibria, and finding quantal response equilibrium. This approach enables managers to decide a proper defense strategy in advance of experiencing cyber-physical dilemma when there are not enough previous data.