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Artificial Neural Network Based Detection of Energy Exhaustion Attacks in Wireless Sensor Networks Capable of Energy Harvesting
Nabil Ali Alrajeh, Shafiullah Khan, Jaime Lloret and Jonathan Loo

Energy consumption is the important factor when designing any mechanism for wireless sensor network (WSN). Research community is trying to enable energy harvesting mechanisms to provide long term energy source to WSN. However, energy consumption is generally greater than energy harvesting in WSN. Furthermore, if nodes are under any kind of energy exhaustion security attack, then energy harvesting mechanism cannot extend the lifetime of the WSN. In this paper, we propose a detection mechanism of energy exhaustion attacks that uses an artificial neural network (ANN). It has been developed for cluster-based WSN and takes into account the energy harvesting system. Simulation results show that our mechanism can detect and prevent such kind of attacks, even having lower percentage of false positives than other systems, and thus enlarge the wireless sensor node lifetime.

Keywords: Wireless sensor network, security, energy exhaustion attack, cluster, energy harvesting, artificial neural network

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