UC Irvine

Intelligent Transportation Systems (ITS) increasingly depend on sophisticated sensor fusion techniques to accurately track vehicles and optimize traffic flow. However, these systems are vulnerable to malicious attacks targeting physical sensors, particularly inductive loop detectors (ILDs), commonly used for vehicle detection at intersections. This thesis addresses the critical problem of understanding how sensor spoofing attacks, specifically magnetic loop spoofing on ILDs, impact the reliability and effectiveness of ITS. To analyze these vulnerabilities, this study employed a comprehensive simulation framework replicating a realistic multi-sensor intersection control environment. Data was gathered through simulated scenarios involving a combination of ILD and camera-based detection under varying weather conditions—including clear, heavy rain, and heavy fog—to mimic diverse operational circumstances. An ILD spoofing attack was modeled, injecting false vehicle detections and suppressing real detections to evaluate the system's resilience. The analysis leveraged standard multi-object tracking metrics such as Multiple Object Tracking Accuracy (MOTA), ID Precision, ID Recall, and ID switches, alongside overall intersection throughput, to quantify the attack's impact. The findings revealed significant performance degradation under attack conditions. Specifically, metrics such as MOTA dropped by approximately 25% and IDF1 decreased by around 20%, indicating substantial performance degradation. Intersection throughput also suffered notably, decreasing by up to 30% under high-intensity attack scenarios, further illustrating the tangible impact on traffic efficiency. Additionally, false positives increased by nearly 35%, and ID switches rose significantly, further emphasizing the attack’s disruptive capability. Furthermore, this research proposes avenues for future work, including extending analyses to other sensor modalities like cameras and radar, and developing multi-layered defense mechanisms to bolster resilience against coordinated sensor attacks. Ultimately, this thesis contributes to the intersection of cybersecurity and transportation engineering, guiding the development of secure, reliable, and resilient ITS infrastructure.