Network Defense Decision-Making Method Based on Stochastic Differential Game Model

Abstract

In the actual network attack and defense, the attack-defense behaviors generally change dynamically and continuously. Besides, since kinds of random disturbance is inevitable, the evolution of network security state actually is random. To model and analyze network security problems more accurately, we used the Gaussian white noise to describe the random disturbance. Then from the perspective of real-time attack and defense, we characterized the random and continuous evolution of network security state referring to dynamic epidemical model and the Ito stochastic differential equations. Based on previous statements, the attack and defense stochastic differential game model was constructed, and the saddle point strategy for the game was proposed. Additionally, we designed an optimal defense strategy selection algorithm to achieve real-time selection of the optimal defense strategies in continuous and random attack-defense process, which has greater timeliness and accuracy. Finally, simulations demonstrated that the proposed model and method are valid, and we offered specific recommendations for network defense based on the experimental data.