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http://dx.doi.org/10.3837/tiis.2020.10.013

SOCMTD: Selecting Optimal Countermeasure for Moving Target Defense Using Dynamic Game  

Hu, Hao (State Key Laboratory of Mathematical Engineering and Advanced Computing)
Liu, Jing (State Key Laboratory of Mathematical Engineering and Advanced Computing)
Tan, Jinglei (State Key Laboratory of Mathematical Engineering and Advanced Computing)
Liu, Jiang (State Key Laboratory of Mathematical Engineering and Advanced Computing)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.14, no.10, 2020 , pp. 4157-4175 More about this Journal
Abstract
Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.
Keywords
moving target defense; dynamic defense; signal game; optimal countermeasure; cost and benefit;
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