Markov Evolutionary Game Model and Migration Strategies for Multi-stage Platform Dynamic Defense

doi:10.3969/j.issn.1000-1093.2021.08.013

Abstract

Abstract: Markov evolutionary game model and migration strategy of multi-stage platform dynamic defense are proposed to improve the efficiency of platform dynamic defense under persistent and periodic attacks. The cyclical and phased characteristics of platform dynamic defense are analyzed from the network attack and defense principle of platform dynamic defense, and the key parameters and revenue of multi-stage platform dynamic defense are calculated. Markov evolutionary game model of multi-stage platform dynamic defense is established. According to the stage of the game, the discount factor and transfer probability are introduced into the total revenue calculation. On this basis, the existence of Nash equilibrium in multi-stage Markov platform dynamic defense evolutionary game is studied, and the Nash equilibrium solution and optimal migration strategy selection algorithm are given. Finally, an example is given to design the analysis process of the migration strategy, and the effectiveness of the proposed model and migration strategy is verified by simulation.

Key words: cyberspacesecurity, platformdynamicdefense, evolutionarygame, migrationstrategy

CLC Number:

TP393.081

WANG Gang, WANG Zhiyi, ZHANG Enning, MA Runnian, CHEN Tongrui. Markov Evolutionary Game Model and Migration Strategies for Multi-stage Platform Dynamic Defense[J]. Acta Armamentarii, 2021, 42(8): 1690-1697.

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