Cyberai innovation: securing the engineering enterprise through AI-integrated operational technology systems cybersecurity education

The National Science Foundation Division of Graduate Education awarded Cleveland State University five hundred thousand dollars on September 1, 2026, under the STEM Education program (CFDA 47.076) to develop and validate educational approaches that prepare engineering students and faculty to secure artificial intelligence-integrated operational technology systems critical to manufacturing, power generation, water treatment, and transportation infrastructure.

The project addresses a national workforce gap by creating hands-on learning modules, faculty professional development initiatives, and openly shared educational resources centered on three research thrusts. The work will define AI-integrated cybersecurity competencies for engineers by integrating the National Initiative for Cybersecurity Education workforce framework, NIST security guidance, and CISA principles into an engineering-focused competency model. The project will design AI-enhanced, scenario-driven laboratory modules embedding AI attack vectors, impacts, and AI-assisted cyber defense into existing chemical, civil, electrical, and mechanical engineering laboratory courses. The effort will strengthen engineering educators' capacity to teach cybersecurity while expanding K–12 outreach and teacher engagement to broaden STEM participation pathways.

Work is performed in Cleveland, Ohio, with a period of performance from September 1, 2026, through August 31, 2029. The assistance type is a Project Grant.

Abstract

Artificial intelligence (AI) is transforming the operation of manufacturing plants, electric power systems, water treatment facilities, transportation networks, and other critical infrastructure. At the same time, AI is enabling increasingly sophisticated cyberattacks against these operational technology (OT) systems, creating new risks to public safety, economic prosperity, and national security. Although engineers are responsible for designing, operating, and maintaining these systems, most cybersecurity education targets computing specialists rather than engineers working in operational environments. This project addresses this national workforce GAP by developing and evaluating educational approaches that prepare engineering students and faculty to secure AI-integratedsystems. Through hands-on learning, faculty professional development, and openly shared educational resources, the project will strengthen the nation's capacity to educate engineers capable of protecting critical infrastructure while expanding pathways for future stem participation through teacher engagement and k?12 outreach. The project will develop and validate a scalable cyberai education model centered on three integrated research thrusts. First, IT will define cyberai competencies for engineers by integrating the national initiative for cybersecurity education (nice) workforce framework, national institute of standards and technology (NIST) guidance forsecurity, and cybersecurity and infrastructure security agency (cisa) principles into an engineering-focused competency framework. Second, IT will design AI-enhanced, scenario-driven laboratory modules based on authenticincidents that embed AI attack vectors, impacts, and AI-assisted cyber defense into existing chemical, civil, electrical, and mechanical engineering laboratory courses. AI-supported instructional tools will assist faculty in creating and delivering cyberai modules while providing adaptive feedback to students. Third, the project will develop AI-assisted cyberai readiness assessments that measure student competence and support personalized learning pathways. The project will employ mixed-methods evaluation using concept inventories, laboratory performance assessments, learning analytics, surveys, and industry advisory feedback. All instructional materials, virtual laboratory modules, readiness assessment instruments, and faculty development resources will be openly disseminated, providing a replicable national model for cyberai engineering education and workforce development. This project is supported by the cyberaicorps scholarship for service (cyberai SFS) program which funds proposals to increase national capacity to educate and train professionals in artificial intelligence (AI) or cybersecurity, and to support their placement and retention in the cyberai mission of government organizations. The scholarship track funds academic institutions to award scholarships to students in exchange for their government service. The innovation track seeks transformative education proposals in the areas of AI, cybersecurity, or the integration of AI and cybersecurity. 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.- subawards are not planned for this award.