A Resource-Efficient System for Detection and Verification of Anomalies Using Mobile Agents in Wireless Sensor Networks

Abstract

Sensor readings are vulnerable to in situ and in transit anomalies. A well designed anomaly detection system should be able to identify the source of anomalies through in situ verification of suspicious behavior of sensor nodes. One approach for in situ verification is physical diagnosis of sensor nodes, which is a cumbersome and time-consuming task in medium-to-large-scale networks. Therefore, we propose a novel method for in situ verification of malicious sensor nodes using mobile agents. We employ Coordinated Resource Management mechanism-based observations to detect first-order anomalies and perform in situ verification. Since mobile agents cannot be frequently transmitted over the resource constrained Wireless Sensor Networks (WSN) due to the expensive nature of the communication operation as compared to the processing operation, we propose a method which exploits the historical information of anomalous behavior of the sensor node to optimize mobile agent transmission. The performance of the proposed system is investigated via simulations, experiments on MICAz mote, and comparative study. The results and analysis demonstrate the effectiveness and efficiency of the proposed system, in comparison with other existing schemes.