Advancing Cybersecurity Education in the Era of Generative AI

Abstract

Artificial intelligence advancements have recently received atten-tion in both academic and industrial settings, demonstrating disruptive potential in many domains, including education. Previous studies have shown that AI-driven tools can transform conventional learning methods. This paper focuses on identifying how generative AI (GAI) tools are leveraged by cybersecurity stu-dents. A survey has been designed based on cognitive process dimension of Bloom’s taxonomy and distributed to students studying cybersecurity in Norway. The results of the survey were illustrated with a set of use cases that demonstrated how Microsoft Copilot can enable students with skills ranging from lower-order knowledge-based skills to higher-order competence-based skills.
The applied use cases presented in this paper indicate that GAI tools can en-hance lower- and higher-order thinking skills of cybersecurity students and con-tribute to bridging the gap between theoretical knowledge and competence-based skills needed to face real-world cybersecurity challenges. However, the results of the survey indicated that this potential has not yet been fully utilized by students, as they use such tools mainly for tasks that require lower-order thinking skills, such as remembering and understanding cybersecurity concepts, and less for more advanced cognitive tasks, such as creating role-playing scenarios. These preliminary findings can be useful to trigger discussions on how to improve fu-ture cybersecurity curricula to include applied GAI use cases and align them with learning outcomes. Ultimately, future efforts can be dedicated to developing a roadmap as a collaborative effort among policy-makers, cybersecurity academics and practitioners on the trustworthy incorporation of applied GAI in cybersecu-rity education.