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AI-assisted security testing in 5G networks for teaching cybersecurity with GitHub Copilot.

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Title: AI-assisted security testing in 5G networks for teaching cybersecurity with GitHub Copilot.
Authors: Tsai, Yi-Hsueh1,2 yihsuehtsai@g.ntu.edu.tw, Chen, Shiang-Jiun1 annette@ntut.edu.tw, Hsiao, Li-Cheng2,3 s1091750@mail.yzu.edu.tw, Chen, Chun-Yang1 t113c53017@ntut.edu.tw, Wang, Shao-Lei1 solomon12354@gmail.com, Wu, Chia-Jung1 stanny6427@gmail.com
Source: Educational Technology & Society. Apr2026, Vol. 29 Issue 2, p46-68. 23p.
Subject Terms: *Science education, 5G networks, Code generators
Abstract: The increasing complexity of 5G networks introduces significant security risks, particularly within the User Plane Function (UPF). The N4 interface and Packet Forwarding Control Protocol (PFCP) are key targets for session hijacking, misconfigured policies, and Distributed Denial of Service (DDoS) attacks. However, teaching 5G security testing remains challenging due to its technical complexity. This paper proposes an AI-assisted approach that integrates GitHub Copilot into cybersecurity education. Students use Copilot to automate testing tasks, simulate attacks, and analyze N4 vulnerabilities. Experimental results show that this approach enhances vulnerability detection, coding efficiency, and cybersecurity skills. AI-generated code bridges the gap between theory and practice, supporting hands-on learning. Our findings confirm that incorporating AI tools fosters skill development, critical thinking, and real-world testing ability, advancing 5G security education. In addition to demonstrating the educational benefits of AI-assisted tools, this study also acknowledges potential risks associated with automated code generation. To ensure secure and responsible use, the framework emphasizes manual validation of AI-generated scripts and the incorporation of secure coding practices. This highlights the need for cybersecurity education to strike a balance between efficiency and critical evaluation, as well as ethical awareness, when integrating AI into 5G security training. [ABSTRACT FROM AUTHOR]
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Database: Education Research Complete
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Abstract:The increasing complexity of 5G networks introduces significant security risks, particularly within the User Plane Function (UPF). The N4 interface and Packet Forwarding Control Protocol (PFCP) are key targets for session hijacking, misconfigured policies, and Distributed Denial of Service (DDoS) attacks. However, teaching 5G security testing remains challenging due to its technical complexity. This paper proposes an AI-assisted approach that integrates GitHub Copilot into cybersecurity education. Students use Copilot to automate testing tasks, simulate attacks, and analyze N4 vulnerabilities. Experimental results show that this approach enhances vulnerability detection, coding efficiency, and cybersecurity skills. AI-generated code bridges the gap between theory and practice, supporting hands-on learning. Our findings confirm that incorporating AI tools fosters skill development, critical thinking, and real-world testing ability, advancing 5G security education. In addition to demonstrating the educational benefits of AI-assisted tools, this study also acknowledges potential risks associated with automated code generation. To ensure secure and responsible use, the framework emphasizes manual validation of AI-generated scripts and the incorporation of secure coding practices. This highlights the need for cybersecurity education to strike a balance between efficiency and critical evaluation, as well as ethical awareness, when integrating AI into 5G security training. [ABSTRACT FROM AUTHOR]
ISSN:11763647
DOI:10.30191/ETS.202604_29(2).RP03