A Global Hybrid Intrusion Detection System for Wireless Sensor Networks

Abstract Many researchers are currently focusing on the security of wireless sensor networks (WSNs). This type of network is associated with vulnerable characteristics such as open-air transmission and self-organizing withoutafixed infrastructure. Intrusion Detection Systems (IDSs) can play an important role in detecting and preventing security attacks. In this paper, we propose a hybrid, lightweight intrusion detection system for sensor networks. Our intrusion detection model takes advantage of cluster-based architecture to reduce energy consumption. This model uses anomaly detection based on support vector machine (SVM) algorithm and aset of signature rules to detect malicious behaviors and provide global lightweight IDS. Simulation results show that the proposed model can detect abnormal events efficiently andhas a high detection rate with lower false alarm.