Distributed monitoring for misbehaviour detection in wireless sensor networks


Khelifa Benahmed, School of Computing & Mathematical Sciences, Liverpool John Moores University, Liverpool, U. K.

E-mail: benahmed_khelifa@yahoo.fr


Wireless sensor networks (WSNs) often consist of tiny devices and offer a variety of potential means to monitor the environment. However, WSNs are vulnerable to several types of attack because of their use in critical applications, their deployment in open and unprotected environments and their limited system resources. Therefore, security design is an important aspect of WSNs. In this work, we focus on detecting misbehaving nodes in WSNs. To the best of our knowledge, we are the first to present a complete and formal study on finding optimised monitor nodes and combining the organisation of the network with monitoring for misbehaviour detection in WSNs. The main idea of this work is to propose simple and efficient distributed monitoring algorithm capable of detecting misbehaviours based on a clustered architecture, where the cluster head is elected according to a new set of metrics. These new election metrics are based on a multiple-criteria decision approach in order to monitor the health status of cluster members and detect misbehaviour. Our proposed strategy ensures a good selection of the nodes responsible for monitoring, reduces energy consumption during the monitoring process—effectively reducing the amount of security information that flows through the network—and reduces latency. The efficiency of our method is evaluated through simulation experiments. Copyright © 2012 John Wiley & Sons, Ltd.