Vehicle tracking using vehicular network beacons

Abstract

Location privacy is one of the main challenges in vehicular ad hoc networks (VANET), which aims to protect vehicles from being tracked. Most of research work concerns changing pseudonyms efficiently to avoid linking messages through them. However, the sensitive information the vehicles send periodically in beacons make them vulnerable to tracking even if beacons are totally anonymous. In this paper, we used the nearest neighbor probabilistic data association (NNPDA) technique to track vehicles through information sent in anonymous beacons. We evaluated the implemented tracker against different vehicle densities, speeds, beacon rates, random noises and packet delivery ratios. The achieved tracking accuracy asserts the necessity of securing beacon messages from global observer attacks.