Game-Theoretical Approach for Cyberattack Modeling and Deep Learning-Based Resilience of Connected Automated Vehicles

The current state of practice in security research on connected automated vehicles (CAVs) does not consider how adversaries may evolve over time and adapt to defense strategies. This proposed research takes the state of practice well beyond the current focus on anomaly detection towards strategic response in defense strategies by developing attack defender models with game-theoretical models. Game theory provides a framework to study the strategic interactions between defenders and adversaries with conflicting objectives. Given the above background, this study will design strategic games to study attacker and defender strategies for cyber deception, as well as algorithms to compute equilibrium or optimal defense strategies in a CAV environment. Real-world data from CAV experiments conducted by PIs will be used to design game theory models in a CAV environment. The study will design two strategic games, namely a zero-sum game and a Stackelberg security game, to formalize the interactions between attackers and defenders by devising a strategic comparison between a zero-sum game and a Stackelberg security game. The proposed game models define payoff functions that capture the trade-offs between model accuracy and the success rates of attacker and defender. The dynamic attacker-defender strategies mimic real-world applications and provide the ability to provide alerts to traffic management center operators for performing cyber incident response in a timely manner, which has attracted the Virginia Department of Transportation’s (VDOT’s) interest. VDOT will serve as a partner to help with real-world implementation.

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

Language

• English

Project

• Status: Active
• Funding: $270,706.00
• 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

  Morgan State University

  1700 E. Cold Spring Lane
  Baltimore, MD 21251, Maryland  United States  21251

  Purdue University

  1040 South River Road
  West Lafayette, IN  United States  47907
• Managing Organizations:

  National Center for Transportation Cybersecurity and Resiliency (TraCR)

  Clemson University
  Clemson, SC  United States 

  Morgan State University

  Department of Transportation and Urban Infrastructure Studies
  1700 E. Cold Springs Lane
  Baltimore, MD  United States  21251
• Project Managers:

  Chowdhury, Mashrur

• Performing Organizations:

  Morgan State University

  1700 E. Cold Spring Lane
  Baltimore, MD 21251, Maryland  United States  21251

  Purdue University

  1040 South River Road
  West Lafayette, IN  United States  47907
• Principal Investigators:

  Ali, Amjad

  Ukkusuri, Satish

  Khattak, Zulqarnain H

• Start Date: 20260401
• Expected Completion Date: 20270331
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Computer security; Connected vehicles; Cyberattacks; Deep learning; Game theory; Vehicle to vehicle communications
• Subject Areas: Data and Information Technology; Highways; Security and Emergencies; Vehicles and Equipment;

Filing Info

• Accession Number: 01988323
• Record Type: Research project
• Source Agency: National Center for Transportation Cybersecurity and Resiliency (TraCR)
• Contract Numbers: 69A3552344812, 69A3552348317
• Files: UTC, RIP
• Created Date: Apr 29 2026 11:17AM