Osdie, Alfido
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Implementation of Generative Language Models (GLM) in Cyber Exercise Secure Coding using Prompt Engineering Sidabutar, Jeckson; Osdie, Alfido
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6012

Abstract

With the advancement of technology, the need for secure software is becoming increasingly urgent due to the rise in vulnerabilities in applications. In 2022, the National Cyber and Encryption Agency (BSSN) recorded 2,348 cases of web defacement, with one of the main causes being the lack of attention to secure coding practices during software development. This study explores the utilization of Generative Language Models (GLMs), such as ChatGPT, in secure coding training to enhance developers' skills. GLMs were implemented in a cybersecurity platform designed specifically for secure coding training, also serving as learning assistants that users can interact with during the cyber exercise. The study results show that the cyber exercise using GLMs significantly improved users' secure coding skills, as evidenced by comparing pre-test and post-test scores, indicating an increase in knowledge and proficiency in secure coding practices.