Wireless Sensor Network Wormhole Detection using an Artificial Neural Network

نویسنده

  • Mohammad Nurul Afsar Shaon
چکیده

This paper presents an innovative wormhole detection scheme an using artificial neural network for wireless sensor networks (WSNs). Most detection schemes described in the literature are designed for uniformly distributed sensors in a network, using statistical and topological information and special hardware. However, these schemes may perform poorly in non-uniformly distributed networks. Accordingly, the aim of the proposed research is to detect wormhole attacks for both uniform and non-uniform network environments. Furthermore, the proposed research does not require any special hardware to discover wormhole attacks and causes no significant communication overhead as well. The efficacy of the proposed detection model is measured in terms of detection accuracy, false positive rate, and false negative rate. The results show that the proposed algorithm achieves higher detection and lower false positive rates in comparison with existing statistical wormhole detectors. Keywords—Artificial neural network; wormhole attack; non-uniform distribution; wireless sensor networks

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تاریخ انتشار 2015