Optimal Strategy Selection for Moving Target Defense Based on Markov Game

Abstract

With the evolution of the research on network moving target defense (MTD), the selection of optimal strategy has become one of the key problems in current research. Directed to the problem of the improper defensive strategy selection caused by inaccurately characterizing the attack and defense game in MTD, optimal strategy selection for MTD based on Markov game (MG) is proposed to balance the hopping defensive revenue and network service quality. On the one hand, traditional matrix game structure often fails to describe MTD confrontation accurately. To deal with this inaccuracy, MTD based on MG is constructed. Markov decision process is used to characterize the transition among network multi-states. Dynamic game is used to characterize the multi-phases of attack and defense in MTD circumstances. Besides, it converts all the attack and defense actions into the changes in attack surface or the ones in exploration surface, thus improving the universality of the proposed model. On the other hand, traditional models care little about defense cost in the process of optimal strategy selection. After comprehensively analyzing the impact of defense cost and defense benefit on the strategy selection, an optimal strategy selection algorithm is designed to prevent the deviation of the selected strategies from actual network conditions, thus ensuring the correctness of optimal strategy selection. Finally, the simulation and the deduction of the proposed approach are given in case study so as to demonstrate the feasibility and effectiveness of the proposed strategy optimal selection approach.