2025 ASEE Annual Conference & Exposition

Integrating Cyber-Physical Security Training to the Electrical Engineering Program via Experiential Learning

Presented at ELOS Technical Session 2: Innovative Strategies for Fostering Deeper Learning in Engineering Laboratories

As industries worldwide embrace the next wave of innovation, the integration of technologies like cyber-physical systems (CPS) and the Internet of Things (IoT) is becoming a key driver of change, with applications ranging from autonomous vehicles to large-scale critical infrastructures. Unfortunately, the increasing use of communication networks to monitor and control these systems has increased their vulnerabilities to cyber threats, posing significant risks that can cause economic losses and even lead to loss of lives. To prepare future electrical engineers for these emerging challenges, it is essential to include cyber-physical security modules with experiential learning in their education. These modules should help students develop the expertise to secure CPS integrated with IoT devices against cyber threats by equipping them with theoretical and practical tools to analyze system vulnerabilities and design defense measures. With these skills, students will be better positioned to face real-world challenges and ensure the resilience and safety of these interconnected systems in our increasingly connected world.
In this work in progress, an embedded development kit accompanied by a set of laboratory experiments has been designed and implemented, which allows students to learn foundational principles related to cyber-physical systems security through hands-on experimentation. The embedded development kit integrates real wired and wireless communication networks with industrial protocols such as Modbus TCP, a real-world programmable logic controller (PLC), models of real-world applications such as submarine position control and a DC motor speed control, and multiple I/O connections to integrate IoT devices and other external physical systems. The laboratory material spans multiple topics including principles of system modeling, feedback control systems and controller design, networking and IoT, deep packet inspection, attack detection, localization, and mitigation, and digital systems, among others. The proposed experiential learning material has been integrated into existing courses and enabled the students to learn a variety of skills that are not typically included in EE education.

Authors

Sangshin Park University of Utah [biography]

Since 2022, he has been with University of Utah, Salt Lake City, UT, where he is currently pursuing an Ph.D at the Computer Science Department. His research interests include Cyber-Physical System, Edge Computing and ML/AI for Cybersecurity ensuring Resilience.
Dr. Reza Kamali California State University San Marcos [biography]

Dr. Reza Kamali-Sarvestani is a Professor of Electrical and Computer Engineering at California State University San Marcos. He received his B.S. degree in Electrical Engineering from Shiraz University Iran, and M.S.E, Ph.D. degree in Electrical
Hamed Nademi [biography]

is an Assistant Professor of Electrical Engineering at California State University-San Marcos (CSUSM). Prior to joining CSUSM, Dr. Nademi served as an Assistant Professor at the New Mexico State University and prior to that he was Research Scientist at Rensselaer Polytechnic Institute (RPI), Troy, NY. He worked as PI/Co-PI with industry-sponsored projects granted by New York State Energy Research & Development Authority (NYSERDA) together with utility companies focusing on control schemes development, autonomous digital power grids and transportation electrification. Dr. Nademi has been a PI on the DOE Marine Energy and Wind Energy competitions and CO-PI of the NSF-funded AI-Assisted Wind Farm Control and ONR-sponsored Marine Energy project over the last three years. He worked with SIEMENS AG, and ABB Inc. as a R&D scientist where he was involved in the development of medium-voltage industrial grid and off-grid applications. He has authored more than 70 published scientific papers and holds seven patents on energy conversion circuits and controls.
Manish Parashar The University of Utah [biography]

Manish Parashar is the Chief AI Officer at the University of Utah. He is also the Director of the Scientific Computing and Imaging (SCI) Institute, Chair in Computational Science and Engineering, and Presidential Professor at the Kahlert School of Computing. Manish’s expertise is in high-performance parallel and distributed computing and cyberinfrastructure. Manish is the founding chair of the IEEE Technical Community on High Performance Computing (TCHPC) and is a Fellow of AAAS, ACM, and IEEE.
Prof. Jairo Giraldo University of Utah [biography]

Dr. Jairo Giraldo received a B.Sc. degree in Electronic Engineering from the National University of Colombia in 2010 and an M.Sc. and Ph.D. degree from the University of the Andes, Colombia in 2012 and 2015, respectively.
Dr. Giraldo is currently a Research Assistant Professor at the Department of Electrical and Computer Engineering at the University of Utah.
His research is centered around the security and privacy of cyber-physical systems using tools from control theory, optimization, and machine learning, with applications in power systems resilience.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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