Enhancing Cybersecurity Education with Artificial Intelligence Content

Artificial Intelligence (AI) has become a fundamental tool for cybersecurity researchers and practitioners. It is frequently used to address major security problems such as supply chain attacks, ransomware threats, and social engineering. In this context, integrating AI into cybersecurity workflows requires incorporating AI-driven approaches into the educational training of the cybersecurity workforce. This paradigm shift in academic settings will introduce the necessary skills for cybersecurity professionals to operate modern AI-based systems. Yet, the current cybersecurity curriculum still suffers from the absence of AI resources, particularly the detailed understanding of the appropriate AI mechanisms. Such absence leaves skill gaps for future professionals and practitioners in the industry. To address this, we designed an academic lecture module on AI covering both theory and practice. Then, we taught the module across six cybersecurity courses in our institution. To assess the effectiveness of integrating AI materials into cybersecurity education, we collected data by presenting two surveys before and after the lecture (concluding 81 participants per survey). Specifically, we utilized widely accepted models for unbiased analysis of our data. Our experimental results show positive AI knowledge improvement by 30% of the participants, demonstrating the beneficial impact of the lecture. Then, we observed a high similarity score between the survey responses and the lecture content, reaching 84%. Moreover, our sentiment analysis results reflect positive feedback from the participants with a positive score of 0.50. Overall, our study serves as a reference for instructional designers for developing educational curricula aiming to integrate AI into cybersecurity education.

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Publication Details

Published
2025-02-12
DOI
https://doi.org/10.1145/3641554.3701958
Citations
5
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
5.94
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article

Enhancing Cybersecurity Education with Artificial Intelligence Content

Mark Finlayson, Monique Ross, A. Selcuk Uluagac, Yassine Mekdad et al.
5 citations
Advanced Malware Detection Techniques
5.94
article

Enhancing Cybersecurity Education with Artificial Intelligence Content

Mark Finlayson, Monique Ross, A. Selcuk Uluagac, Yassine Mekdad, Fernando Brito
article en
5 citations

Abstract

Artificial Intelligence (AI) has become a fundamental tool for cybersecurity researchers and practitioners. It is frequently used to address major security problems such as supply chain attacks, ransomware threats, and social engineering. In this context, integrating AI into cybersecurity workflows requires incorporating AI-driven approaches into the educational training of the cybersecurity workforce. This paradigm shift in academic settings will introduce the necessary skills for cybersecurity professionals to operate modern AI-based systems. Yet, the current cybersecurity curriculum still suffers from the absence of AI resources, particularly the detailed understanding of the appropriate AI mechanisms. Such absence leaves skill gaps for future professionals and practitioners in the industry. To address this, we designed an academic lecture module on AI covering both theory and practice. Then, we taught the module across six cybersecurity courses in our institution. To assess the effectiveness of integrating AI materials into cybersecurity education, we collected data by presenting two surveys before and after the lecture (concluding 81 participants per survey). Specifically, we utilized widely accepted models for unbiased analysis of our data. Our experimental results show positive AI knowledge improvement by 30% of the participants, demonstrating the beneficial impact of the lecture. Then, we observed a high similarity score between the survey responses and the lecture content, reaching 84%. Moreover, our sentiment analysis results reflect positive feedback from the participants with a positive score of 0.50. Overall, our study serves as a reference for instructional designers for developing educational curricula aiming to integrate AI into cybersecurity education.

Florida International University (US), The Ohio State University (US)
Openalex Percentile: Top 5%
Advanced Malware Detection Techniques
5.94
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