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.
Language
- English
Project
- Status: Active
- Funding: $220000
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Contract Numbers:
69A3552348305
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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
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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
- TRT Terms: Artificial intelligence; Autonomous vehicles; Computer security; Connected vehicles
- Subject Areas: Data and Information Technology; Highways; Security and Emergencies; Vehicles and Equipment;
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