Survey on application of Large Language Models in network attack and defense

The emergence of Large Language Models (LLMs) has significantly transformed the technological and cybersecurity landscape, introducing both unprecedented opportunities and formidable challenges. With the public release of ChatGPT in 2022, LLMs have gained global prominence, redefining natural language processing capabilities and enabling advancements across various fields. In cybersecurity, these models represent a dual-use technology: while they offer powerful tools for threat detection, automated analysis, and security training, they also pose risks when leveraged by malicious actors for phishing, social engineering, and the creation of evasive malware. This thesis presents a comprehensive literature review exploring the dual roles of LLMs in cybersecurity. It examines how these models are currently utilized for both offensive and defensive purposes, evaluates the ethical and regulatory implications of their deployment, and highlights ongoing efforts to mitigate associated risks. By synthesizing current research and real-world applications, this study aims to equip cybersecurity professionals, researchers, and policymakers with a nuanced understanding of LLMs’ impact on digital security, ultimately contributing to informed strategies for their responsible and secure use.