Empowering Cybersecurity with LLMs
R. Renugadevi, R. Muthumeenakshi, Karthika Ganesan · Advances in computational intelligence and robotics book series · 2025
As cyber threats become increasingly sophisticated and prevalent, traditional cybersecurity approaches struggle to keep pace with the rapidly evolving tactics, techniques, and procedures employed by cybercriminals. In response, the integration of Large Language Models (LLMs) within threat intelligence and intrusion detection systems presents a promising solution to automate and enhance the detection, analysis, and mitigation of complex cyberattacks. LLMs, such as OpenAI's GPT models and Google's BERT, possess the ability to process large volumes of unstructured data, understand context, and identify patterns that may elude conventional detection methods. This chapter explores the potential of LLMs in revolutionizing cybersecurity by addressing the automation challenges inherent in modern threat intelligence and detection systems. The chapter further discusses the methodologies and tools being developed to overcome these hurdles, including hybrid AI approaches, transfer learning, and advancements in model interpretability and explainability.