Security Defense of Transportation Networks against Cyber Attacks: A Physics-Informed AI Approach

Connected and Automated Vehicles (CAVs) hold immense promise for revolutionizing traffic networks, promising reduced congestion and enhanced road safety. The promise of CAVs stems from inherent their interconnectivity and automation. However, this also makes them vulnerable to cyber attacks from malicious actors attempting to disrupt, manipulate, or harm their operations. To harness their full potential and ensure the safety of passengers and road users, robust cybersecurity measures are imperative. This project presents a cyber attack detection and defense framework , comprising a cyber attack detection module and a cyber attack defense module. Within the cyber attack detection module, our framework leverages the power of physics-informed AI (artificial intelligence), integrating classical physics-based traffic models with advanced machine learning techniques. This integration enables the prediction of vehicle trajectories under normal conditions, forming a baseline for cyber attack detection. Upon detection of cyber attacks, the framework swiftly initiates real-time defensive mechanisms. The cyber attack defense module would adjust the CAV's trajectory to avoid potential threats or, when necessary, transfer control to the driver for human intervention. To assess the efficacy and real-world applicability of the proposed cyber attack detection and defense framework, the research team will conduct a comprehensive evaluation in both simulation and small-scaled, real-world experiments using the CAVs at UW-Madison.


  • English


  • Status: Active
  • Funding: $220000
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    University of Michigan Transportation Research Institute

    2901 Baxter Road
    Ann Arbor, Michigan  United States  48109
  • Project Managers:

    Stearns, Amy

  • Performing Organizations:

    University of Wisconsin, Madison

    Department of Civil and Environmental Engineering
    1415 Engineering Drive
    Madison, WI  United States  53706
  • Principal Investigators:

    Chen, Sikai

    Ahn, Sue

    Noyce, David

  • Start Date: 20240401
  • Expected Completion Date: 20250331
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01912738
  • Record Type: Research project
  • Source Agency: Center for Connected and Automated Transportation
  • Contract Numbers: 69A3552348305
  • Files: UTC, RIP
  • Created Date: Mar 21 2024 12:22PM