Markov Differential Game for Network Defense Decision-Making Method

While network attack and defense are experiencing a rapid change, the current research achievements of network security based on traditional game theory fail to characterize the real-time performance of the actual network attack-defense process accurately. Furthermore, all kinds of disturbance and accidental factors would affect the evolution of the network security state. Therefore, to tackle with the randomness of network security state and the high dynamic of network defense decision making, we analyzed the attack-defense behaviors from the perspectives of dynamic and real-time confrontation. Then we constructed the Markov attack-defense differential game model for the dynamic analysis to predict multi-stage continuous attack-defense process by combining differential game models and the Markov decision-making method. In addition, according to the discounted total payoffs of attack-defense game, we designed the objective function of the game. Based on previous statements, we proposed the multistage game equilibrium solution and designed the optimal defense strategy selection algorithm. Finally, we conducted simulations to demonstrate that the proposed model and method could shed some light to the real-time interplay of decision making between attack and defense.