Collaborative Research: CyberTraining: Implementation: Small: CyberSTAR: CyberTraining for Secure Transportation and Reliable Autonomy
- Institution
- University of California - Merced, CA
- Principal investigator
- Qian Wang
- Funding
- $150K
- Duration
- 2025–2028
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Abstract
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. The project addresses critical issues in cyber workforce development in the transportation and automotive sectors through three initiatives. The first leverages faculty from different disciplines to develop a coherent open-source CI that provides a unified research platform for automotive and autonomous systems. Leveraging this CI, the second initiative delivers modular training materials on secure transportation system design. Finally, the third initiative arranges a series of workshops to directly train 80 participants, including faculty members, graduate students, and cyberinfrastructure professionals. The project also produces and disseminates royalty-free resources to support workforce development and education in transportation system security. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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