Game Theory Model for Intrusion Detection in WSN using Hierarchical Trust Management

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In Wireless Sensor Networks (WSN), the existing attack detection consumes more time and inaccurate as well. Also, the process of estimating trusted node prior to data transmission is inefficient. Hence in this paper, we propose a game theory model for intrusion detection in WSN using Hierarchical Trust Management. In this technique, the peer-to-peer trust evaluation method is implemented using anomaly based intrusion detection system that includes trust component such as intimacy, honesty, energy, unselfishness, average SNR, minimum SNR, and max-minus-min SNR to determine the reliable node. In order to detect the probability of malicious node, game theory is applied. In this approach, intrusion detection system and intruders are non-cooperative players. The intruder maximizes its benefits by destroying the functionality of the system and the protector tries to protect the facility. By simulation results, we show that the proposed technique enhances the network security
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Wireless Sensor Networks (WSN); Game Theory; Intrusion Detection; Hierarchical Trust Management

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