Optimal Dissemination Strategy of Security Patch Based on Differential Game in Social Network

Li, Miao; Li, Shuai; Wang, Zhongqin

doi:10.1007/s11277-017-4866-z

Cited by 4 publications

(1 citation statement)

References 15 publications

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“…This requires an extremely large number of network nodes to satisfy the conditions that can be analyzed by differential equations. Therefore, this method is only applicable to ultra-large-scale complex networks, which limits its practicability [15]. The Bayesian game is a classic incomplete information game, which requires at least one participant's information to be unknown to other participants, but the participants can have an initial judgment on the probability of other participants' types [16].…”

Section: Introductionmentioning

confidence: 99%

Optimal Network Defense Strategy Selection Based on Markov Bayesian Game

2019

KSII TIIS

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The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.

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Section: Introductionmentioning

confidence: 99%