Enhancing Cybersecurity Education with Artificial Intelligence Content

被引:0
作者
Brito, Fernando [1 ]
Mekdad, Yassine [1 ]
Ross, Monique [2 ]
Finlayson, Mark A. [3 ]
Uluagac, Selcuk [1 ]
机构
[1] Florida Int Univ, Sch Comp & Informat Sci, Cyber Phys Syst Secur Lab, Miami, FL 33199 USA
[2] Ohio State Univ, Engn Educ Dept, Columbus, OH USA
[3] Florida Int Univ, Sch Comp & Informat Sci, Cognit Narrat & Culture Lab Cognac Lab, Miami, FL USA
来源
PROCEEDINGS OF THE 56TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE TS 2025, VOL 2 | 2025年
基金
美国国家科学基金会;
关键词
Cybersecurity; Education; Artificial intelligence; Integration; Natural Language Processing; Machine Learning; CYBER SECURITY;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:158 / 164
页数:7
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