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Distributed Aggregative Games on Graphs in Adversarial Environments

机译:对抗环境中图上的分布式聚合游戏

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Existing solutions to aggregative games assume that all players are fully trustworthy for cooperative tasks or, in a worst-case scenario, are selfish players with no intent to intentionally harm the network. Nevertheless, the need to believe that players will behave consistently exposes the network to vulnerabilities associated with cyber-physical attacks. This paper investigates the effects of cyber-physical attacks on the outcome of distributed aggregative games (DAGs). More specifically, we are seeking to answer two main questions: (1) how a stealthy attack can deviate the game outcome from a cooperative Nash equilibrium, and by doing so, (2) by how much efficiency of a DAG degrades. To this end, we first show that adversaries can stealthily manipulate the outcome of a DAG by compromising the Nash equilibrium solution and consequently lead to an emergent misbehavior or no emergent behavior. This study will intensify the urgency of designing novel resilient solutions to DAGs so that the overall network sustains some notion of acceptable global behavior in the presence of malicious agents. Finally, we corroborate and illustrate our results by providing simulation examples. Simulations reveal that the adverse effect of a compromised agent is considerably worse than that of a selfish agent.
机译:现有的综合性游戏解决方案假设所有玩家都完全值得信赖,可以完成合作任务,或者在最坏的情况下,他们都是自私的玩家,无意故意损害网络。尽管如此,仍然需要相信玩家的行为会持续,这使网络面临与网络物理攻击相关的漏洞。本文研究了网络物理攻击对分布式综合游戏(DAG)的结果的影响。更具体地说,我们正在寻求回答两个主要问题:(1)隐身攻击如何使合作Nash均衡偏离游戏结果,以及这样做,(2)DAG的效率降低多少。为此,我们首先表明,对手可以通过破坏纳什均衡解决方案来秘密操纵DAG的结果,从而导致突发的不良行为或没有突发的行为。这项研究将加剧为DAG设计新颖的弹性解决方案的紧迫性,以使整个网络在存在恶意代理的情况下维持可接受的全球行为的某些概念。最后,我们通过提供仿真示例来证实和说明我们的结果。模拟表明,受害代理的不利影响比自私代理的不利影响严重得多。

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