基于不完全信息动态博弈的动态目标防御最优策略选取研究

摘要

针对动态目标防御的最优策略选取问题,分析了动态目标防御环境下的攻防对抗特点,提出了动态目标防御策略的收益量化方法,基于不完全信息动态博弈构建了面向动态目标防御的单阶段和多阶段博弈模型,给出了精炼贝叶斯均衡求解算法和先验信念修正方法,获得了不同安全态势下的最优动态目标防御策略.最后,通过实例说明和验证了上述模型和方法的可行性和有效性,总结了利用动态目标防御策略进行网络防御的一般性规律.%This paper is focused on the optimal policy selection for moving target defense.Attack-defense confronta tion in moving target defense environment is analyzed.Reward quantization method of moving target defense policy is proposed.Single-stage and multi-stage moving target defense game models are constructed based on the dynamic game with incomplete information.The algorithm to obtain perfect Bayesian equilibrium and the method to revise prior belief are proposed.Optimal moving target defense policies are obtained under different security situations.Finally,not only the feasibility and effectiveness of the proposed model and method are illustrated and verified in a representative example but also general rules of network defense using moving target defense policies are summarized.