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Epidemic Protection Over Heterogeneous Networks Using Evolutionary Poisson Games

机译:使用演化泊松博弈的异构网络的流行病防护

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摘要

Malware is increasingly sophisticated and affects the wellbeing of a large population of heterogeneous and highly connected devices. The users of these devices can make strategic and dynamic decisions to choose whether or not to adopt the antivirus software, not only to secure their individual devices but also to protect the network they are part of. Motivated by the strategic behaviors of the antivirus adoption, we establish an evolutionary Poisson game framework to capture the random, dynamic, and heterogeneous interactions of agents in a holistic fashion, and design mechanisms to control their behaviors to achieve a system-wide objective. We first prove the existence and uniqueness of a mixed Nash equilibrium of the large population game and show that the equilibrium is an evolutionary stable strategy. Finally, we develop online algorithms using the techniques of stochastic approximation coupled with the population dynamics, and they are shown to converge to the optimal solution of the controller problem. Numerical examples are used to illustrate and corroborate our results.
机译:恶意软件日益复杂,影响着大量异构和高度连接的设备的安全。这些设备的用户可以做出战略和动态的决定,以选择是否采用防病毒软件,不仅可以保护其单个设备的安全,还可以保护它们所组成的网络。受防病毒软件采用的战略行为的启发,我们建立了一个演化的Poisson游戏框架,以整体方式捕获代理的随机,动态和异构交互,并设计了控制其行为的机制,以实现整个系统的目标。我们首先证明了大型种群博弈混合纳什均衡的存在性和唯一性,并证明了该均衡是一种演化稳定策略。最后,我们使用随机逼近技术和种群动态技术开发了在线算法,并证明它们收敛于控制器问题的最优解。数值示例用于说明和证实我们的结果。

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