Game Analysis and Optimization for Evolutionary Dynamic Heterogeneous Redundancy

Abstract

Dynamic Heterogeneous Redundancy (DHR) has been considered as a proactive defense architecture against unknown vulnerabilities and backdoors. It is a heterogeneous, fault-tolerant, and redundant system, which ensures the security by constantly switching heterogeneous executors. However, a limited number of heterogeneous executors can be merely switched and combined statically. It is difficult to cope with persistent threats. In this paper, we propose an evolutionary DHR system, add evolutionary sub-strategies of executors to solve this problem, optimizing defense mechanisms of DHR. To demonstrate theoretical validity, a game-theoretic analysis of the DHR security mechanism is performed under dynamic incomplete information, and the dilemma of defense is discussed. We construct a DHR game model based on evolutionary, and the results are extended to the general case to analyze the Bayesian equilibrium when each service strategy has a different number of evolved sub-strategies. In addition, the correlation factor is added to the game to investigate the impact of the correlation between different heterogeneous executors on defense results. Finally, Gambit and NS2 simulation experiments for the proposed method are shown. To verify the applicability of the physical system, a prototype DHR system based on dynamic evolution was constructed. We collect key configuration information and modified them randomly. It ensures that the information scanned by the attacker is different each time. Finally, the effectiveness of the physical system is verified by nmap and metasploit tools.