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Extending Anticipation Games with Location, Penalty and Timeline

机译:使用地点,罚款和时间表扩展期待游戏

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Over the last few years, attack graphs have became a well recognized tool to analyze and model complex network attack. The most advanced evolution of attack graphs, called anticipation games, is based on game theory. However even if anticipation games allow to model time, collateral effects and player interactions with the network, there is still key aspects of the network security that cannot be modeled in this framework. Theses aspects are network cooperation to fight unknown attack, the cost of attack based on its duration and the introduction of new attack over the time. In this paper we address these needs, by introducing a three-fold extension to anticipation games. We prove that this extension does not change the complexity of the framework. We illustrate the usefulness of this extension by presenting how it can be used to find a defense strategy against 0 days that use an honey net. Finally, we have implemented this extension into a prototype, to show that it can be used to analyze large networks security.
机译:在过去几年中,攻击图已成为一个良好的分析和模型网络攻击的识别工具。攻击图中最先进的演变,称为预期游戏,是基于博弈论。但是,即使预期游戏允许模型时间,抵押效果和玩家与网络交互,仍然存在无法在此框架中建模的网络安全性的关键方面。这些方面是网络合作来打击未知攻击,攻击成本基于其持续时间和随着时间的推移引入新的攻击。在本文中,我们通过向预期游戏引入三倍的扩展来解决这些需求。我们证明,此扩展不会改变框架的复杂性。我们通过展示如何用于找到使用蜂蜜网的0天来寻找防御策略来说明这一扩展的有用性。最后,我们已经将此扩展实施到原型中,以表明它可用于分析大型网络安全性。

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