CRAIMay 6, 2024

When LLMs Meet Cybersecurity: A Systematic Literature Review

arXiv:2405.03644v2242 citationsHas CodeCybersecurity
Originality Synthesis-oriented
AI Analysis

It offers a valuable resource for researchers and practitioners in cybersecurity by synthesizing existing knowledge and highlighting challenges, but it is incremental as it reviews rather than introduces new methods.

This paper provides a systematic literature review analyzing over 300 works to address the lack of a comprehensive overview of LLM applications in cybersecurity, covering 25 LLMs and more than 10 downstream scenarios.

The rapid development of large language models (LLMs) has opened new avenues across various fields, including cybersecurity, which faces an evolving threat landscape and demand 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 addresses this gap by providing a systematic literature review, covering the analysis of over 300 works, encompassing 25 LLMs and more than 10 downstream scenarios. Our comprehensive overview addresses three key research questions: the construction of cybersecurity-oriented LLMs, the application of LLMs to various cybersecurity tasks, the 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 field. We also maintain and regularly update a list of practical guides on LLMs for cybersecurity at https://github.com/tmylla/Awesome-LLM4Cybersecurity.

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Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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