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A Game-Theoretic Framework for Robust Optimal Intrusion Detection in Wireless Sensor Networks

机译:无线传感器网络中鲁棒最优入侵检测的博弈论框架

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摘要

A robust optimization model is considered for nonzero-sum discounted stochastic games with incomplete information in order to formally formulate and analyze the intrusion detection problem in wireless sensor networks (WSNs). Security requirements of WSNs are taken into account to characterize the game parameters and model the player objectives. To generalize the problem, the game data are assumed not to be fully known to the players, who take a robust optimization approach to address this data uncertainty. For assessing the validity and effectiveness of the framework, illustrative instances of the developed game model are generated. Equilibrium analysis reveals how the conflicting objectives of the intruder and intrusion detection system compel them to adopt different conservative stances toward data uncertainty. It is also shown, by numerical results, that the robust approach in the presence of uncertainty reduces the sensitivity of the solution with respect to data perturbations, and thus improves design stability.
机译:考虑具有不完整信息的非零和折扣打折随机游戏的鲁棒优化模型,以便正式制定和分析无线传感器网络(WSN)中的入侵检测问题。考虑到WSN的安全性要求以表征游戏参数并为玩家目标建模。为了概括这个问题,假定游戏者不完全了解游戏数据,他们采取了可靠的优化方法来解决该数据不确定性。为了评估框架的有效性和有效性,生成了开发的游戏模型的说明性实例。均衡分析揭示了入侵者和入侵检测系统的冲突目标如何迫使他们对数据不确定性采取不同的保守立场。数值结果还表明,存在不确定性的鲁棒方法降低了解决方案对数据扰动的敏感性,从而提高了设计的稳定性。

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