Mitigating Cybersecurity Attacks on Automotive Radar Systems

With more vehicles equipped with features such as adaptive cruise control (ACC) and autonomous emergency braking (AEB), the number of radar sensors on the roads is growing. Radar sensors operate in the same frequency bands and may interfere with one another, causing false positives or even masking true positives (i.e., actual detections). With the increasing level of autonomous driving, this poses a serious threat to traffic safety. Although radar interference mitigation is an active area of research, the imminent cybersecurity threat resulting from intentional and targeted interference has been overlooked thus far. In this paper, we address this problem and propose a mitigation approach based on random-sequence modulation to reject such interference attacks on radar systems. We evaluate and discuss the proposed mitigation approach, illustrating its benefits through extensive simulations.

DOI 10.1109/IV66570.2026.11623945