Securing Intelligent Transportation Systems against Spoofing Attacks

Game theory is a powerful tool for security risk analysis that has been extensively used in various engineering systems, and game-theoretic approaches have been applied to studying the security of routing in transportation and communications. This project will be the basis for a synthesis of game theory and queuing theory, essential for capturing the interaction between the queuing dynamics and players decisions, in order to protect the ITS system from spoofing and attacks.

Design of Resilient Smart Highway Systems with Data-Driven Monitoring from Networked Cameras

This project aims to develop a systematic way to design smart highway systems with networked video monitoring and control resiliency against environment disruptions and sensor failures. The research team will investigate deep learning methods for extracting fine-grained local categorical traffic information from surveillance videos and novel graph neural network methods to correlate and propagate the local information through the highway network for global states estimation, such as vehicle tracking and reidentification or traffic prediction in an unobserved area.