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A Stackelberg Game and Markov Modeling of Moving Target Defense

机译:一款Stackelberg游戏和马尔可夫移动目标防御模型

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We propose a Stackelberg game model for Moving Target Defense (MTD) where the defender periodically switches the state of a security sensitive resource to make it difficult for the attacker to identify the real configurations of the resource. Our model can incorporate various information structures. In this work, we focus on the worst-case scenario from the defender's perspective where the attacker can observe the previous configurations used by the defender. This is a reasonable assumption especially when the attacker is sophisticated and persistent. By formulating the defender's problem as a Markov Decision Process (MDP), we prove that the optimal switching strategy has a simple structure and derive an efficient value iteration algorithm to solve the MDP. We further study the case where the set of feasible switches can be modeled as a regular graph, where we solve the optimal strategy in an explicit way and derive various insights about how the node degree, graph size, and switching cost affect the MTD strategy. These observations are further verified on random graphs empirically.
机译:我们提出了一个用于移动目标防御(MTD)的Stackelberg游戏模型,其中Defender定期切换安全敏感资源的状态,以使攻击者难以识别资源的实际配置。我们的模型可以包含各种信息结构。在这项工作中,我们专注于攻击者可以观察防御者使用的先前配置的最坏情况。这是一个合理的假设,特别是当攻击者复杂和持久性时。通过将Defender的问题作为Markov决策过程(MDP),我们证明了最佳切换策略具有简单的结构,并导出了有效的值迭代算法来解决MDP。我们进一步研究了可行性交换机集合作为常规图形的情况,在那里我们以明确的方式解决最佳策略,并导出关于节点度,图形大小和切换成本如何影响MTD策略的各种见解。这些观察结果在经验上进行随机图进行核实。

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