An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

Abstract

In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) downward-IDS (D-IDS) to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) upward-IDS (U-IDS) to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented.