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

Principal Investigator(s):

Sikai Chen, Assistant Professor of Civil and Environmental Engineering – University of Wisconsin-Madison
Sue Ahn, Professor of Civil and Environmental Engineering – University of Wisconsin-Madison
David Noyce, Arthur F. Hawnn Professor – University of Wisconsin-Madison
Executive Associate Dean of the College of Engineering – University of Wisconsin-Madison
Executive Director – Traffic Operations and Safety (TOPS) Laboratory
Executive Director – Wisconsin Driving Simulator Laboratory
Associate Director – Safety Research Using Simulation (SaferSIM) Center

Project Abstract:
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 their inherent 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, we will conduct a comprehensive evaluation in both simulation and small-scaled, real-world experiments using the CAVs at UW-Madison.

Institution(s): University of Wisconsin-Madison

Award Year: 2023

Research Focus: Cybersecurity

Project Form(s):