Optimal strategy selection approach to moving target defense based on Markov robust game

Moving target defense, as a "game-changing" security technique for network warfare, thwarts the apparent certainty of attackers by transforming the network resource vulnerabilities. In order to enhance the defense of unknown security threats, a novel of optimal strategy selection approach to moving target defense based on Markov robust game is first proposed in this paper. Firstly, moving target defense model based on moving attack and exploration surfaces is defined. Thus, the random emerging of vulnerabilities is described, as well as the cognitive and behavioral difference of offensive and defensive sides caused by defensive transformation. Based on it, Markov robust game model is constructed to depict the multistage and multistate features of moving target defense confrontation, in which the unknown prior information in incomplete information assumption are illustrated by combining Markov decision process with robust game theory. Further, the existence of optimal strategy of Markov robust game is proved. Additionally, by equivalent converting optimal strategy selection into a nonlinear programming problem, an efficient optimal defensive strategy selection algorithm is designed. Finally, simulation and deduction of the proposed approach are given in the case study so as to demonstrate the feasibility of constructed game model and effectiveness of the proposed approach.