Detection of Selective Forwarding Attacks in Wireless Sensor Networks using Channel-Aware Adaptive Detection Threshold

Wireless Sensor Network (WSN) are vulnerable to selective forwarding attacks that can maliciously drop a subset of packets for degrading network performance and endanger the information security. Meanwhile,due unstable to wireless channel in WSN the packet loss rate during the communication of sensor nodes may be high and varying from time to time. In this paper Channel-aware Reputation System with Adaptive Detection Threshold in Wireless Sensor Networks (CADT) to detect selective forwarding attacks is proposed. The CADT evaluates the data forwarding behaviors of the sensor nodes, according to the deviation from monitored packet loss and estimated normal loss. To optimize the detection accuracy of CADT, the optimal threshold for forwarding evaluation is adaptive to time varied channel condition and the estimated attack probabilities of compromised nodes. Furthermore an attack-tolerant data forwarding scheme is developed to collaborate with CADT for stimulating the forwarding cooperation of compromised nodes and improving the data delivery ratio of the network. Extensive simulation results demonstrate that CADT can accurately detect the selective forwarding attacks and identify the compromised sensor nodes, while the attack-tolerant data forwarding scheme can significantly improve the data delivery ratio of the network.