Tracking-Based Wireless Intrusion Detection for Vehicular Networks

In this work we develop a new tracking-based wireless intrusion detection algorithm that allows for the identification of malicious vehicle network users who are not at their appropriate locations. Based on a particle filter implementation and detection thresholds set by Cramer-Rao lower bounds we show how our tracking-verification algorithm is capable of verifying any reported positions within a reasonable time frame of order 30 seconds. We explicitly determine how the performance of the algorithm, as measured by detection and false positive rates, is influenced by the amount of tracking information collected. The results presented here are important for implementation of safe vehicular networks where only users at the expected locations can access and participate in the network communications.