Attack detection in camera and Lidar in smart cars using time delay differential equations

With the rapid integration of advanced technologies into modern vehicles, the cybersecurity of smart cars has become a pressing concern. In this context, the utilization of Time Delay Differential Equations (DDEs) emerges as a promising approach for detecting cyber attacks targeting smart car systems. This paper investigates cyber-attacks on smart car sensor systems, focusing on the vulnerabilities of camera and LIDAR sensors to spoofing and jamming. Using time delay differential equations (DDEs) to model time delays in sensor communication and stability analysis, the study identifies methods for real-time detection of cyber-attacks. Simulations showed that significant deviations in sensor readings, particularly those impacted by abnormal delays and noise, effectively flagged sensor tampering and jamming attempts. These findings confirm the effectiveness of DDE-based models for detecting anomalies in real time, supporting the resilience of autonomous vehicle systems against cyber threats.