Large Language Models for Explainable Threat Intelligence

As cyber threats continue to grow in complexity, traditional defense mechanisms often struggle to keep up. Large Language Models (LLMs) offer significant potential in cybersecurity due to their advanced capabilities in text comprehension and generation. This research explores the use of LLMs through Retrieval-Augmented Generation (RAG) to enhance cybersecurity functions by combining real-time information retrieval with domain-specific data for more accurate and timely Cyber Threat Intelligence (CTI).

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Published
2025-04-08
DOI
https://doi.org/10.1109/edcc-c66476.2025.00015
Primary Topic
Topic Modeling
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article
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article

Large Language Models for Explainable Threat Intelligence

Miguel Correia, Renata S. Tavares, Tiago Dinis
Topic Modeling
article

Large Language Models for Explainable Threat Intelligence

Miguel Correia, Renata S. Tavares, Tiago Dinis
article en

Abstract

As cyber threats continue to grow in complexity, traditional defense mechanisms often struggle to keep up. Large Language Models (LLMs) offer significant potential in cybersecurity due to their advanced capabilities in text comprehension and generation. This research explores the use of LLMs through Retrieval-Augmented Generation (RAG) to enhance cybersecurity functions by combining real-time information retrieval with domain-specific data for more accurate and timely Cyber Threat Intelligence (CTI).

Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento (PT), University of Lisbon (PT), Autonomous University of Lisbon (PT)
Openalex Percentile: Top 88%
Topic Modeling
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Large Language Models for Explainable Threat Intelligence — Miguel Correia, Renata S. Tavares, et al. · (2025) | TGRS Research Map | TGRS