WF-MTD: Evolutionary Decision Method for Moving Target Defense Based on Wright-Fisher Process

Abstract

The limitations of the professional knowledge and cognitive capabilities of both attackers and defenders mean that moving target attack-defense conflicts are not completely rational, which makes it difficult to select optimal moving target defense strategies difficult for use in real-world attack-defense scenarios. Starting from the imperfect rationality of both attack-defense, we construct a Wright-Fisher process-based moving target defense strategy evolution model called WF-MTD. In our method, we introduce rationality parameters to describe the strategy learning capabilities of both the attacker and the defender. By solving for the evolutionarily stable equilibrium, we develop a method for selecting the optimal defense strategy for moving targets and describe the evolution trajectories of the attack-defense strategies. Our experimental results in our example of a typical network information system show that WF-MTD selects appropriate MTD strategies in different states along different attack paths, with good effectiveness and broad applicability. In addition, compared with no hopping strategy, fixed periodic route hopping strategy, and random periodic route hopping strategy, the route hopping strategy based on WF-MTD increase defense payoffs by 58.7%, 27.6%, and 24.6%, respectively.