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

Abstract

As a promising occasion monitoring and statistics gathering technique, wi-fi sensor network has been extensively carried out to each army and civilian packages. However, because of the lack of physical safety, sensor nodes are effortlessly compromised by using adversaries, making WSN at risk of various safety threats. One of the most intense threats is selective forwarding attack, where the compromised nodes can maliciously drop a subset of forwarding packets to become worse the records delivery ratio of the community. In this assignment, we propose a Channel-conscious Reputation System with adaptive detection threshold to hit upon selective forwarding attacks in WSNs. The CRS-A evaluates the information forwarding behaviors of sensor nodes, in keeping with the deviation of the monitored packet loss and the expected ordinary loss and it optimizes the detection accuracy.