Classification of Hacker’s Posts Based on Zero-Shot, Few-Shot, and Fine-Tuned LLMs in Environments with Constrained Resources

Classification of Hacker’s Posts Based on Zero-Shot, Few-Shot, and Fine-Tuned LLMs in Environments with Constrained Resources

This paper investigates, applies, and evaluates state-of-the-art Large Language Models (LLMs) for the classification of posts from a dark web hackers’ forum into four cyber-security categories. The LLMs applied included Mistral-7B-Instruct-v0.2, Gemma-1.1-7B, Llama-3-8B-Instruct, and Llama-2-7B, wit...

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Bibliographic Details
Main Authors: Theodoros Giannilias, Andreas Papadakis, Nikolaos Nikolaou, Theodore Zahariadis
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Future Internet
Subjects:
large language model
mistral
gemma
llama
cybersecurity
dark web
Online Access:https://www.mdpi.com/1999-5903/17/5/207
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