Optimal Strategy Selecting Method for Mimic Defense Based on Incomplete Information Dynamic Game

Mimic defense (MD) is a novel architecture which takes the dynamic and heterogeneous security of redundant executors, and prevents further attacks through multi-mode decision feedback mechanism. However, there is a lack of effective analysis and evaluation on the defense cost and risk of multi-mode decision output. In this paper, we proposed the idea of Bayesian decision-making with minimum risk combined with the failure probability of the executor and the output of multi-mode decision. After considering the impact of failed defense and defensive cost on strategy generation, the optimal cleaning strategy is designed to ensuring the validity of optimal strategy. Finally, simulation experiments confirm the effectiveness of the model.