Detecting Selective Forwarding Attacks In Wireless Sensor Networks

Abstract

Wireless sensor networks are being used in a wide variety of applications ranging from home automation to military surveillance. Security of a sensor network must be ensured for proper functioning of the many applications that depend on them. Due to the low computational capabilities and resource constrained nature of sensor nodes, sensor networks are prone to many attacks like selective forwarding. In this thesis we propose a novel and low power consuming approach to accurately detect selective forwarding attacks and trace back the attacker using an acknowledgement based scheme. We also make use of a probability based metric to increase the accuracy of detection and to reduce the undetected attacker rate in the sensor network. We performed experiments on a network of real sensor motes and showed that our approach has higher accuracy of detection and lower communication overhead compared to previous work.