Techniques and Approaches for Leveraging LLMs in Security Analysis

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Author(s): Rebet Keith Jones (Capitol Technology University, USA)
Copyright: 2025
Pages: 30
Source title: Application of Large Language Models (LLMs) for Software Vulnerability Detection
Source Author(s)/Editor(s): Marwan Omar (Illinois Institute of Technology, USA)and Hewa Majeed Zangana (Duhok Polytechnic University, Iraq)
DOI: 10.4018/979-8-3693-9311-6.ch003

Keywords: Artificial Intelligence / Engineering Science Reference / Information Security & Privacy / Security & Forensics

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Abstract

This chapter explores the various techniques and approaches for utilizing large language models (LLMs) in security analysis. It delves into how LLMs can enhance the detection and mitigation of security vulnerabilities by leveraging natural language processing and machine learning capabilities. The chapter highlights the integration of LLMs into security frameworks, offering insights into their application in threat detection, anomaly analysis, and automated incident response. Additionally, it examines the challenges and future directions in leveraging LLMs for robust security analysis, emphasizing the need for ongoing research to address current limitations.

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Techniques and Approaches for Leveraging LLMs in Security Analysis

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