In recent years, the issue of location verification system (LVS) has received significant attention in wireless communication networks, especially in Intelligent Transportation Systems (ITSs) and vehicular technology, where the location information is important for users’ safety and security. In this paper, we consider a vehicular network and analyze a more general Information Theoretic (ITc) study of LVS, specifically, aiming at finding an optimum decision threshold for detection a spoofed location and increasing the system ability in correctly detecting malicious users. For this purpose, we propose different information theoretic measures (Renyi divergence, Renyi mutual information, Kullback–Leibler divergence, Kullback–Leibler mutual information and Jensen-Shannon divergence) for identifying malicious user. Simulation results and comparison between proposed measures show that the optimum decision threshold can be achieved by applying the Jensen-Shannon divergence measure

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