The DPC-Based Scheme for Detecting Selective Forwarding in Clustered Wireless Sensor Networks

Many studies have shown that clustered Wireless Sensor Networks (WSNs) a better performance in terms of the balance energy and lifetime. However, due to harsh environment open communication, WSNs are easy be attacked. The selective forwarding attack is one most difficult attacks detected. When malicious sensor node launches attacks, it drops part or all data packets received. In this paper, we propose Noise-Based Density Peaks Clustering (NB-DPC) algorithm for detecting attacks. It can detect by clustering Cumulative Forwarding Rates (CFRs) nodes. NB-DPC has been improved defining noise points specifically identifying behavior deleting unnecessary steps (DPC) faster detection speed. low Missed Detection Rate (MDR) False (FDR) below 1% according simulation results.