Ghost Cars and Fake Obstacles: Automated Security Analysis of Emerging Smart Transportation Systems

Transportation systems today will soon be transformed profoundly due to two recent technology advances: Connected Vehicle (CV) and Autonomous Vehicle (AV). Such transformation leads to the creation of a series of next-generation transportation systems such as smart traffic lights and self-driving cars, which can substantially improve the quality of our everyday life. However, this also brings new features and operation modes into the transportation ecosystem, e.g., network connectivity and machine learning based sensing, which may introduce new security problem and challenges. In this talk, I will describe my current research that initiates the first effort towards systematically understanding the robustness of the software-based control in CV and AV systems. Specifically, I will first describe my work that performs the first security analysis of the next-generation CV-based traffic signal control, which discovers new vulnerabilities at the traffic signal control algorithm level that can be exploited to create massive traffic jams. Next, I will describe my work that performs the first security analysis of LiDAR-based object detection in AV systems. I will conclude by discussing defense directions for the discovered problems, and also future research directions in securing emerging CAV systems.

Qi Alfred Chen is an Assistant Professor in the Department of Computer Science at the University of California, Irvine. His research interest is network and systems security, and the major research theme is addressing security challenges through systematic problem analysis and mitigation. His research has discovered and mitigated security problems in systems such as next-generation transportation systems, smartphone OSes, network protocols, DNS, GUI systems and access control systems. Currently, his focus has been in smart systems and IoT, including transportation and autonomous vehicle systems. His work has high impact in both academic and industry with over 10 top-tier conference papers, a DHS US-CERT alert, multiple CVEs, and over 50 news articles by major news media such as Fortune and BBC News. Chen received his Ph.D. from the University of Michigan in 2018.