Computer Science editorial
Open AccessOA2026
Teaching Critical Infrastructure Security Through Interactive Experiences
InfraLearn is a gamified learning platform that teaches non-computer science students cybersecurity for critical infrastructure through simulated attacks on a Distributed Energy Resource (DER) device. It integrates narrative-driven scenarios, virtual machines, and optional AI support to make abstract threats tangible and emphasize ethical defense.
Ella Luedeke; Meera Sridhar; H. Ramaprasad· Journal of The Colloquium for Information Systems Security Education· 2026· DOI 10.53735/cisse.v13i1.243
The core problem
The increasing interconnectivity of critical infrastructure, particularly in the energy sector, has introduced significant cybersecurity challenges. Traditional cybersecurity education often targets computer science students, leaving future engineers and professionals in other domains without foundational knowledge to secure essential systems. This work introduces InfraLearn, a gamified learning platform designed to bridge this gap by teaching non-computer science students a foundational background in cybersecurity for critical infrastructure. InfraLearn focuses on Distributed Energy Resource (DER) systems, which are vital components of modern smart grids. By simulating realistic attacks on a DER device modeled after the Enphase Gateway solar monitor, the platform aims to make abstract threats tangible and emphasize the ethical application of defensive skills. The authors argue that this approach can engage future engineers in securing critical infrastructure through interactive, narrative-driven experiences.
Innovation
InfraLearn is implemented as a web-based platform using a Flask-based API to simulate a DER device. The platform offers three prototype scenarios derived from real-world vulnerabilities: API spoofing, unauthorized remote shut-downs, and Living-off-the-Land (LoTL) downgrade exploitation. These scenarios are integrated into a narrative-driven learning environment where students interact with pre-configured virtual machines and guided code templates. Checkpoint quizzes reinforce comprehension, and optional AI support is available to assist students, minimizing the need for prior programming experience. The design emphasizes hands-on learning, allowing students to explore attack vectors and defensive strategies in a controlled, ethical setting. The platform's architecture includes a front-end interface for student interaction and a back-end API that emulates the DER device's behavior, enabling realistic simulation of attacks and responses.
Introduction
The increasing interconnectivity of critical infrastructure, particularly in the energy sector, has introduced significant cybersecurity challenges. Traditional cybersecurity education often targets computer science students, leaving future engineers and professionals in other domains without foundational knowledge to secure essential systems. This work introduces InfraLearn, a gamified learning platform designed to bridge this gap by teaching non-computer science students a foundational background in cybersecurity for critical infrastructure. InfraLearn focuses on Distributed Energy Resource (DER) systems, which are vital components of modern smart grids. By simulating realistic attacks on a DER device modeled after the Enphase Gateway solar monitor, the platform aims to make abstract threats tangible and emphasize the ethical application of defensive skills. The authors argue that this approach can engage future engineers in securing critical infrastructure through interactive, narrative-driven experiences.
Why it matters
The InfraLearn platform addresses a critical gap in cybersecurity education by targeting non-computer science students and focusing on critical infrastructure. By situating cybersecurity concepts within the context of energy systems, it makes abstract threats tangible and highlights the ethical responsibilities of engineers. The gamified approach, combined with narrative elements, fosters engagement and motivation, which are essential for effective learning. The use of real-world vulnerabilities ensures that students gain practical insights into potential threats. However, the study acknowledges limitations, such as the need for broader evaluation across diverse student populations and the potential for scaling the platform to cover additional infrastructure sectors. Future work includes expanding the scenarios, integrating more advanced AI support, and assessing long-term learning outcomes. The authors conclude that InfraLearn represents a scalable approach to engaging future engineers in securing critical infrastructure, with the potential to adapt to various educational settings.
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