Detection of beacon transmission denial attack in ITS using temporal auto-correlation and random inspections

For many Intelligent Transportation System (ITS) applications, periodic transmission of beacon messages by a source vehicle is paramount for providing the unhindered service and to maintain its accuracy. A malicious source vehicle could deny beacon messages of a target ITS application and intelligently cover-up this denial with signal loss faced due to wireless channel error and surrounding environment obstacles. In this context, we propose a lightweight technique to detect a beacon denial attacker using Auto-Correlation Function (ACF). This technique possesses higher detection accuracy in comparison to fixed threshold scheme which depends upon the number of beacon messages denied by the source vehicle. Furthermore, we propose a random vehicle inspection scheme for inspecting randomly chosen set of vehicles for beacon denial attack. In addition to reducing computational overhead, the advantage of this scheme is that an attacker with knowledge about detection algorithm cannot decide the time and place of inspection. Simulation results confirm the accurate and lightweight nature of the proposed technique.