Cybersecurity Testbed
- Principal Investigator: Satish Ukkusuri, Purdue University
- Co-Principal Investigator: Alvaro Cardenas, The University of California, Santa Cruz
- Co-Principal Investigator: Daniel Fremont, The University of California, Santa Cruz
- Co-Principal Investigator: Leilani Gilpin, The University of California, Santa Cruz
- Co-Principal Investigator: Gurcan Comer, Benedict College
- Co-Principal Investigator: Mansoureh Jeihani, Morgan State University
- Co-Principal Investigator: Mashrur Ronnie Chowdhury, Clemson University
- Co-Principal Investigator: M Sabbir Salek,Clemson University
- Co-Principal Investigator:Alvaro Cardenas, The University of California, Santa Cruz
- Sponsor: Federal $266,304.78; Cost-share $266,838.78
- Duration: 01/2024-12/2024
Project Description:
Many states and local administrators have vowed to advance advanced transportation systems by enhancing autonomy and connectivity. While integrating new technologies and algorithms holds promise in promoting efficiency and safety, it also introduces vulnerabilities. Previous research has demonstrated viable attacks on connected and autonomous vehicles (CAVs), such as GPS spoofing and tactics involving the manipulation of traffic signals. However, most studies are based on small-scale scenarios (e.g., one vehicle, one intersection, or one link), which can only reflect the local and limited impact of the attacks. To comprehensively evaluate the threats associated with cyberattacks against CAVs, and to see whether specific defense mechanisms effectively address a threat, a faithful testbed capable of handling multi-scale system dynamics is needed.
The proposed project aims to develop a sophisticated simulation testbed capable of assessing the multi-scale impact of cyber-attacks against CAV fleets. Unlike existing testbeds, our project will adopt a co-simulation framework to model multi-scale system dynamics from V2X communication, vehicle maneuvering, and car-following to vehicle scheduling, routing, and network-level cascading congestion effects. Ultimately, this project aims to construct a reliable environment that can serve as a foundational platform for future cybersecurity studies.
USDOT Priorities
The project supports USDOT priorities and the RD&T strategic goals by:
Safety: The testbed enables monitoring of existing vulnerabilities, assessing their risks, and testing diverse defense algorithms. This contributes to building a safer transportation system for all people. Economic Strength and Global Competitiveness: The testbed plays an essential role in developing more secure and reliable connected and autonomous vehicle applications, strengthening their global competitiveness. This contributes to the fostering of an inclusive and sustainable economy. Transformation: The testbed provides tools for addressing cybersecurity challenges for future connected/autonomous vehicle applications. This contributes to the deployment of new transportation applications, driving transformative advancements in the practical field. The project engages in breakthrough, advanced, or transformative research by:
Holistic Vulnerability Assessment: Our project will simulate the large-scale impact of cyberattacks in connected and autonomous vehicle (CAV) systems, providing a comprehensive view of potential weak points and risks across the network. Practical Attack Validation: By verifying existing attacks on CAV fleets, we bridge the gap between theory and practice, offering tangible insights into the real-world impact of these threats. Unveiling Cascading Attack Effects: The testbed will capture and analyze the cascading effects of cyber-attacks, shedding light on how disruptions can propagate within road networks, shedding light on a more resilient and secure transportation infrastructure design. Enhancing Traffic Flow Understanding: Our project will model compromised traffic flow under cyber-attacks, allowing us to accurately predict and mitigate operational disruptions, ultimately contributing to safer and more efficient traffic management. Outputs:
A High-fidelity Testbed for Cyberattacks: This project will develop a co-simulation testbed with three components (cloud controller, scenario generator, and a high-fidelity traffic simulator) based on state-of-the-art technologies. Our code and data will be open-source and documented to make them available for examination and future studies. Simulation Language for Cyberattacks: This project will create a solid mechanism that allows us to define diverse cyberattack scenarios targeting CAVs formally. Through this mechanism, we can specify various cyber threats, ranging from GPS spoofing to malware intrusions, to assess their potential impact on CAV fleets reliably. Testing of Typical Cyberattacks: This project will test typical attacks on CAV fleets that are reported in the literature and provide crucial insights into their potential cascading impacts on road networks, helping to forge a better understanding of the potential risks of CAVs among policymakers and the public.
Outcomes/Impacts:
This project will lay the foundation for expansive future endeavors in transportation cybersecurity research. Our vision encompasses the initial testbed’s efficacy and its potential for growth and adaptation. To this end, we envision collaborative projects with research partners that leverage our testbed’s capabilities to explore new dimensions of cybersecurity in intelligent transportation systems (ITS). This project will provide information about the large-scale impact of cyberattacks on road networks. The findings can be integrated into practical applications such as data collection and communication standards and regulations. A crucial aspect of this project involves a commitment to regular updates and enhancements across all testbed components. This project aims to foster a community to continuously refine and elevate the testbed’s capabilities to address evolving research imperatives and the ever-changing landscape of cybersecurity threats in CAV applications.
