Voting-On-Grid Clustering for Secure Localization in Wireless Sensor Networks

Many sensor network applications require sensors to obtain their locations correctly. Various techniques have been proposed to locate regular sensors based on some special nodes called beacon nodes, which are supposed to know their locations. However, most of the existing techniques are vulnerable in hostile environments. The position estimation accuracy decreases drastically when some of the beacon nodes are compromised. Providing a certain degree of localization accuracy at the presence of malicious beacons becomes a very challenging task. In this paper, a secure and efficient voting-on-grid clustering (VoGC) scheme is proposed to mitigate the impact of such attacks. In our scheme, malicious beacon signals are filtered out according to the clustering result of intersections of location reference circles. We employ a voting-on-grid method instead of traditional clustering algorithms to reduce the computational cost. Simulation results demonstrate that the proposed scheme can provide very good localization accuracy and identify a high proportion of malicious beacon signals.