CyberSTAR: CyberTraining for Secure Transportation and Reliable Autonomy
CyberSTAR: CyberTraining for Secure Transportation and Reliable Autonomy
NSF Award #2519390 · CyberTraining · 2025–2028
Project Summary
Modern transportation systems have undergone a significant transformation, marked by increased design complexity, advanced networking capabilities, and an overwhelming surge in data. As a result, today’s automotive system is a collection of interconnected embedded systems, some of which (such as the infotainment system) are also connected to the Internet. As the number of connected vehicles grows, traffic systems become networked and autonomous fleets emerge in the consumer space, the potential for cyberattacks on U.S. transportation infrastructure increases significantly.
Given the criticality of the transportation cyberinfrastructure (CI), this project builds expertise in the automotive cyber domain through development of testbed and training curriculum material and summer training workshops for educators, students, and researchers.
Technical Approach
The project addresses critical issues in cyber workforce development in the transportation and automotive sectors through three initiatives:
- Shared Cyber-Infrastructure (CI): Leverages faculty from different disciplines to develop a coherent open-source CI that provides a unified research platform for automotive and autonomous systems.
- Modular Training Materials: Delivers training materials on secure transportation system design, built on top of the shared CI.
- Training Workshops: Arranges a series of workshops to directly train 80 participants, including faculty members, graduate students, and cyberinfrastructure professionals.
The project produces and disseminates royalty-free resources to support workforce development and education in transportation system security.
Related Course
This grant directly supports the redesign of CYSE 465: Transportation Systems Design at George Mason University, incorporating experiential learning activities on automotive security, reverse engineering, and attack-and-defense scenarios.
Research Team
| Role | Investigator | Institution |
|---|---|---|
| Lead PI | Dr. Md Tanvir Arafin | George Mason University |
| Co-PI | Dr. Lu Gao | University of Houston |
| Co-PI | Dr. Qian Wang | UC Merced |
Funding
NSF Award #2519390 Collaborative Research: CyberTraining: Implementation: Small: CyberSTAR: CyberTraining for Secure Transportation and Reliable Autonomy Total Project Award: $500,000 · Mason Share: $200,000 · Period: Jul. 2025 – Jun. 2028