When LLMs Meet Cybersecurity: A Systematic Literature Review

• URL: http://arxiv.org/abs/2405.03644v1
• Date: Mon, 6 May 2024 17:07:28 GMT
• Title: When LLMs Meet Cybersecurity: A Systematic Literature Review
• Authors: Jie Zhang, Haoyu Bu, Hui Wen, Yu Chen, Lun Li, Hongsong Zhu,
• Abstract summary: Large language models (LLMs) have opened new avenues across various fields, including cybersecurity. There is a lack of a comprehensive overview of this research area. This study aims to shed light on the extensive potential of LLMs in enhancing cybersecurity practices.
• Score: 9.347716970758604
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rapid advancements in large language models (LLMs) have opened new avenues across various fields, including cybersecurity, which faces an ever-evolving threat landscape and need for innovative technologies. Despite initial explorations into the application of LLMs in cybersecurity, there is a lack of a comprehensive overview of this research area. This paper bridge this gap by providing a systematic literature review, encompassing an analysis of over 180 works, spanning across 25 LLMs and more than 10 downstream scenarios. Our comprehensive overview addresses three critical research questions: the construction of cybersecurity-oriented LLMs, LLMs' applications in various cybersecurity tasks, and the existing challenges and further research in this area. This study aims to shed light on the extensive potential of LLMs in enhancing cybersecurity practices, and serve as a valuable resource for applying LLMs in this doamin. We also maintain and regularly updated list of practical guides on LLMs for cybersecurity at https://github.com/tmylla/Awesome-LLM4Cybersecurity.

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