Network Defense Decision-making Method Based on Improved Evolutionary Game Model

For the problem that the existing network defense decision-making method is challenging by error interference and real-time response, a novel network defense decision-making method based on an Improved Evolutionary Game Model (IEGM) is proposed. Firstly, using the classical servo system model for reference, the short-term prediction effect of the defense side on the attack strategy is quantified by differential hypothesis to accelerate the convergence of the model and improve the efficiency of defense decisions. Secondly, the mechanism of error generation in attack-defense game is analyzed, then the observational error in network defense is defined quantitatively, and the improved replication dynamics equation is proposed to strengthen the tolerance of the model to information deviation. On this basis, an improved evolutionary game model is established, and the corresponding stability analysis and mathematical proof are given to prove that the model can converge to the-neighborhood of the Nash equilibrium solution. Theoretical analysis and simulation  results show that the proposed model can overcome the influence of observation error, and the optimal pure defense strategy with deviation order of 0.01% is given. Besides, under the jamming environment, the response speed of defense decision-making can be improved by 64.06% compared with the other three decision models. The improved model and decision-making method can effectively improve the response timeliness of defense decisions and the adaptability to observation error.