Tracking spoofed locations in crowdsourced vehicular applications

Position information is essential for many vehicular applications like traffic information and route planning but also for enabling vital network routing services. However, the accuracy of the latter is highly dependent of a precise location service which might be altered by attackers forging falsified position data. In this paper, we propose a new method for tracking and removing location spoofing anomalies in large scale position based services assuming neither control of the communication infrastructure or additional hardware nor software at the client side. Our system uses aggregation of location information to compute relevant stability metrics which may reveal anomalous events.