Improvement and Evaluation of Resilience of Adaptive Cruise Control Against Spoofing Attacks Using Intrusion Detection System

Abstract: The Adaptive Cruise Control (ACC) system automatically adjusts the vehicle speed to maintain a safe distance between the vehicle and the lead (ahead) vehicle. The controller's decision to accelerate or decelerate is computed using the target speed of the vehicle and the difference between the vehicle's distance to the lead vehicle and the safe distance from that vehicle. Spoofing the vehicle speed communicated through the Controller Area Network (CAN) of the vehicle impacts negatively the capability of the ACC (Proportional-Integral-Derivative variant) to prevent crashes with the lead vehicle. The paper reports about extending the ACC with a real-time Intrusion Detection System (IDS) capable of detecting speed spoofing attacks with reasonable response time and detection rate, and simulating the proposed extension using the CARLA simulation platform. The results of the simulation are: (1) spoofing the vehicle speed can foil the ACC to falsely accelerate, causing accidents, and (2) extending ACC with ML-based IDS to trigger the brakes when an accident is imminent may mitigate the problem. The findings suggest exploring the capabilities of ML-based IDS to support the resilience mechanisms in mitigating cyber-attacks on vehicles.