With the continuous advances in sensing, AI, networking, and control, Autonomous Driving (AD) and V2X (Vehicle-To-Everything)-based Intelligent Transportation System (ITS) technologies have recently become particularly mature and practical. In these technologies, the AI stack is highly security- and safety-critical: for example, in AD systems, the autonomous AI stack is in charge of highly safety-critical driving decisions such as collision avoidance and lane keeping, and thus any security problems in it can directly impact public safety and the society. Over the past few years, my group has been actively studying and developing this research space in industry-grade AD systems and V2X-based ITS systems in general. Specifically, we performed the first security analysis on a wide range of critical AI components in industry-grade AD systems such as 3D perception, sensor fusion, lane detection, localization, prediction, and planning; the first to develop formal verification methods for cooperative AD algorithms, V2X protocols, and traffic-rule conformation; first to characterize AD software bugs; and the first to study the security of USDOT’s V2X-based intelligent traffic light. In this talk, I will talk about our journey so far, with highlights on our key findings and also how we address the domain-specific research challenges we encountered.

Qi Alfred Chen is an Assistant Professor in the Department of Computer Science at the University of California, Irvine. His research interest spans software security, systems security, and network security. His 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 autonomous driving systems, next-generation transportation systems, smartphone OSes, network protocols, DNS, GUI systems and access control systems. Currently, his research focuses on security problems in autonomous systems and IoT, for example autonomous driving and smart transportation systems. His works have high impacts in both academic and industry with over 20 top-tier conference papers (over 10 in the security area), a US DHS US-CERT alert, multiple CVEs, over 50 news articles by major news media such as Fortune and BBC News, and email acknowledgements from US DOT, Apple, Microsoft, and Comcast. Chen received his Ph.D. from the University of Michigan in 2018.