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A game-theoretic approach for combating node compromise attack in Wireless Sensor Network

机译:一种在无线传感器网络中对抗节点入侵攻击的博弈论方法

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Wireless Sensor Network(WSN), due to their popularity have become common in many domains like defense, traffic management, health applications, environment monitoring etc. With these wide range of applications and increasing popularity of WSN, that carry sensitive information are vulnerable to various threats and attacks. In this paper, an intelligent Intruder Detection System(IDS) is proposed that uses sophisticated data fusion technique, involving the use Neural Network as decision making tool and game theory model for the interaction between victim and attacker node. In specific Bayesian game theory is used in formulating the scenario of the intruder, in IDS. These combined effects make IDS robust to combat against the packets attempting to hack some sensitive information residing in the legitimate node. This paper presents the study and combined implementation of both game theory concept and Neural Network to function as an intelligent IDS, which is trained to produce optimal output strategy with varying parameters of intruder. The obtained results, shows that the defence mechanism can be considered as one of the solution concept towards security concerns of WSN.
机译:无线传感器网络(WSN)由于其受欢迎程度已在国防,流量管理,健康应用,环境监视等许多领域中变得普遍。随着这些广泛的应用和WSN的日益普及,携带敏感信息的人易受各种攻击的影响。威胁和攻击。本文提出了一种使用复杂数据融合技术的智能入侵检测系统(IDS),其中涉及使用神经网络作为决策工具和博弈论模型来进行受害者与攻击者节点之间的交互。在特定的贝叶斯博弈论中,IDS使用了贝叶斯博弈论来制定入侵者的情景。这些综合效果使IDS能够强大地抵抗试图破解合法节点中某些敏感信息的数据包。本文介绍了博弈论概念和神经网络的研究和组合实现,以发挥智能IDS的作用,对IDS进行训练以产生具有可变入侵者参数的最优输出策略。获得的结果表明,防御机制可以被视为解决WSN安全问题的解决方案之一。

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