A New Energy Prediction Approach for Intrusion Detection in Cluster-Based Wireless Sensor Networks

Wireless Sensor Networks (WSNs) require an efficient intrusion detection scheme to identify malicious attackers. Traditional detection schemes are not well suited for WSNs due to their higher false detection rate. In this paper, we propose a novel intrusion detection scheme based on the energy prediction in cluster-based WSNs (EPIDS). The main contribution of EPIDS is to detect attackers by comparing the energy consumptions of sensor nodes. The sensor nodes with abnormal energy consumptions are identified as malicious attackers. Furthermore, EPIDS is designed to distinguish the types of denial of service (DoS) attack according to the energy consumption rate of the malicious nodes. The primary simulation experiments prove that EPIDS can detect and recognize malicious attacks effectively.