Attack Detection and Mitigation for Sensor and CAN Bus Attacks in Vehicle Anti-lock Braking Systems

Abstract

For a modern vehicle, if a sensor in the vehicle Anti-lock Braking System (ABS) or the controller area network (CAN) bus is attacked during a brake process, the vehicle will lose driving direction control and driver’s life will be highly threatened. However, current methods for detecting attacks are not sufficiently accurate and no methods can provide attack mitigation. To ensure vehicle ABS security, we propose an attack detection method to accurately detect both sensor attack and CAN bus attack in a vehicle ABS, and an attack mitigation strategy to mitigate their negative effects on the vehicle ABS. In our attack detection method, we build a vehicle state space equation which considers real-time road friction coefficient to predict vehicle states (i.e., wheel speed and longitudinal brake force) with their previous values. Based on sets of historical measured vehicle states, we develop a search algorithm to find out attack changes (vehicle state changes because of the attack) by minimizing errors between predicted vehicle states and measured vehicle states. In our attack mitigation strategy, attack changes are subtracted from measured vehicle states to generate correct vehicle states for the vehicle ABS. We conducted first real sensor attack experiments to show how a magnet affects sensor readings. Our experimental results demonstrate that our attack detection method can detect sensor attack and CAN bus attack more accurately compared with existing methods, and also our attack mitigation strategy almost eliminates attack’s effects on the vehicle ABS.