Detecting sinkhole attack in wireless sensor network using enhanced particle swarm optimization technique

Abstract

Wireless Sensor Network (WSN) is a collection of tiny sensor nodes capable of sensing and processing the data. These sensors are used to collect the information from the environment and pass it on to the base station. A WSN is more vulnerable to various attacks. Among the different types of attacks, sinkhole attack is more vulnerable because it leads to a variety of attacks further in the network. Intrusion detection techniques are applied to handle sinkhole attacks. One of effective approach of intrusion detection mechanism is using Swarm Intelligence techniques (SI). Particle Swarm Optimization is one of the important swarm intelligence techniques. This research work enhances the existing Particle Swarm Optimization technique and the proposed technique is tested in a simulated environment for performance. It is observed that the proposed Enhanced Particle Swarm Optimization (EPSO) technique performs better in terms of Detection rate, False Alarm rate, Packet delivery ration, Message drop and Average delay when compared to the existing swarm intelligence techniques namely, Ant Colony Optimization and Particle Swarm Optimization.