Collaborative Research: Implementation: Medium: Secure, Resilient Cyber-Physical Energy System Workforce Pathways via Data-Centric, Hardware-in-the-Loop Training

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This project will establish a CyberTraining hub of cyber physical energy systems in Southern Florida, a region that suffers from numerous coastal processes impacting critical infrastructures and therefore would greatly benefit from resilience and security research and education. This project aims to provide students and researchers with mentored, hands-on training. The faculty team has expertise across power engineering, communication networks, data science, and cyber/hardware security to build a novel model for energy cyberinfrastructure resilience education. The curriculum and instructional materials to be developed will bring advanced skills from multiple areas, under the umbrella of cyber-physical energy systems. Participants will develop and refine multi-disciplinary skillsets needed for the data-centric energy industry, using the unique, remotely connected smart grid cyberinfrastructure. Participants will extend their academic research portfolios, strengthening their career competitiveness as future cyberinfrastructure professionals and users. Two-week workshops will immerse undergraduate/graduate students and researchers in a unique training opportunity through laboratory demonstrations and mini workshops. Semester-long projects will provide research-intensive training and further strengthen the participants' real-world problem-solving capabilities. The project will tackle three technical challenges with significant intellectual merit: (1) Curating comprehensive, heterogeneous benign and malicious cyber-physical data from a remotely-connected cyberinfrastructure platform to strongly enable hands-on training and research. Hardware-in-the-loop power testbed connected with a virtual network laboratory will be used to characterize system dynamics, where state-of-the-art hardware and software modules will enable humans, machines, and grids to cooperate in a near-to-real learning environment; (2) Developing user-friendly cybersecurity modules in a virtual lab to simulate threats from cyberspace, enabling self-paced training. Participants will create attack scenarios in the cyber domain, where the attacking process and consequence are visualized in the physical system. Data analysis techniques based on machine learning (ML)/artificial intelligence (AI) will be developed as a set of cyber defense mechanisms; (3) Designing, delivering, and integrating cross-disciplinary curricula, composed of undergraduate and graduate course modules and a certificate program. The project further offers unique training opportunities with relevant private and public sector partners through capstone projects and internships.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.