Zitat
M. Kahlert, M. Zhang, D. Markert, T. Fei, M. Gardill, and A. Masrur, “Mitigating Cybersecurity Attacks on Automotive Radar Systems,” in 2026 IEEE Intelligent Vehicles Symposium (IV), 2026, pp. 431–436.
Abstract
With more vehicles featuring functions such as adaptive cruise control (ACC) and autonomous emergency braking (AEB), there is a growing number of radar sensors on the streets. Radar sensors operate in the same frequency bands and may interfere with each other, causing false positives or even masking true positives (i.e., real detections). With an increasing level of autonomous behavior, this poses a serious threat to traffic safety. Even though radar interference mitigation is an active area of research, the imminent cybersecurity threat resulting from intentional and targeted interference has been disregarded so far. In this paper, we are concerned with 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 based on extensive simulations.
Referenzen und Relationen
DOI 10.1109/IV66570.2026.11623945