Detection of Anomalous Cluster Heads and Nodes in Wireless Sensor Networks

Abstract

Almost all security protocols of wireless sensor networks believe that the enemy or attacker can take full control of a sensor node through direct connection. Security is very important in accepting and using sensor networks in many applications. In order to clarify this issue, we focus on detecting anomalies in the nodes and cluster heads of wireless sensor networks, and look for a solution to detect anomalies in the nodes and cluster heads and determine new cluster heads. A group of researchers to detect anomalies have suggested Mobile Data Collectors (MDCs) machines, where some abnormal nodes may be inactive at the time of inspection and not be identified, and due to environmental problems, the machine cannot go to those places, it is also very expensive and cannot work online and cannot quickly overcome attacks. Due to the large number of sensors, it is not scalable. In this article, we first review the methods that have been proposed until now and describe their advantages and disadvantages and then propose a method that detects the anomalies of the nodes in the cluster heads and detects the anomalies of the cluster heads in the sink node, it runs without the need for external circuits and does not impose additional costs, it works online and can quickly overcome attacks. Our proposed method for evaluating performance was simulated by MATLAB software and it uses Intel Research Laboratory Database.