Anomaly detection in wireless sensor networks

Wireless sensor networks (WSNs) are prone to vulnerabilities due to their resource constraints and deployment in remote and unattended areas. A sensor node exhibits anomaly in behavior due to its dying energy level or being compromised by the intruders. The node showing anomalous behaviours being a leader node (LN) of acluster/group multifolds the vulnerability problem. To identify the anomalous nodes in WSNs, this paper presents a model, which uses a Voronoi diagram based network architecture. The network architecture, which deploys mobile data collectors (MDCs), ensures the compatibility of the anomaly detection model for the resource constrained WSNs, and warrants data integrity between the MDCs and the LNs. Our empirical evidence shows the effectiveness of the proposed approach.