Hybrid classical-quantum AI approach for detecting cyberattacks in vehicles

In this project, the research team plans to develop a hybrid classical-quantum machine learning library to detect vehicle cyberattacks. By leveraging quantum supremacy, the team's library should improve the speed of training and the accuracy of intrusion-detection systems. Specifically, the team will analyze the performance of the quantum neural network in the feature extraction and the feature analysis, respectively. After understanding this performance, the team will find a hybrid classical-quantum architecture that generates the best performance. In addition, the team will test their hybrid library in different quantum devices, including the superconducting quantum computer and the optical quantum computer. Different quantum error mitigation techniques based on different quantum devices will be included in the team's library. Moreover, the team will develop a tensor network approach to improve the training efficiency of the variational quantum circuits. In sum, this research focuses on investigating the architecture of the hybrid system and the optimization method in training. With their developed library, the team will apply it to detect various vehicle cyberattacks, improving driving security.

• Record URL:
  https://www.clemson.edu/cecas/tracr/research/projects.html

Language

• English

Project

• Status: Active
• Funding: $457539
• Contract Numbers:

  69A3552344812

  69A3552348317

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590

  Clemson University

  College of Engineering and Science
  109 Riggs Hall, Box 340901
  Clemson, SC  United States  29631-0901

  Purdue University

  1040 South River Road
  West Lafayette, IN  United States  47907

  Benedict College

  1600 Harden Street
  Columbia, South Carolina  United States  29204
• Managing Organizations:

  National Center for Transportation Cybersecurity and Resiliency

  1 Research Dr
  Greenville, South Carolina  United States  29607
• Project Managers:

  Chowdhury, Mashrur

• Performing Organizations:

  Clemson University

  216 Lowry Hall
  Clemson, SC, SC  United States  29634

  Purdue University

  1040 South River Road
  West Lafayette, IN  United States  47907

  Benedict College

  1600 Harden Street
  Columbia, South Carolina  United States  29204
• Principal Investigators:

  Li, Shaozhi

  Tewari,  Sumanta

  Wang, Yao

  Chowdhury, Mashrur

  Salek, Sabbir

  Aggarwal, Vaneet

  Ukkusuri, Satish

  Comert, Gurcan

• Start Date: 20240101
• Expected Completion Date: 20241231
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Artificial intelligence; Computer security; Machine learning; System architecture; Vehicle safety
• Subject Areas: Data and Information Technology; Security and Emergencies; Transportation (General); Vehicles and Equipment;

Filing Info

• Accession Number: 01907734
• Record Type: Research project
• Source Agency: National Center for Transportation Cybersecurity and Resiliency (TraCR)
• Contract Numbers: 69A3552344812, 69A3552348317
• Files: UTC, RIP
• Created Date: Feb 9 2024 7:30PM