Investigating Large Language Models for Attack Detection in IoT Environments

• Grant number: 25/06753-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2025
• End date: April 30, 2026
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Michele Nogueira Lima
• Grantee: Felipe Araujo Melo
• Host Institution: Instituto de Ciências Exatas (ICEx). Universidade Federal de Minas Gerais (UFMG). Ministério da Educação (Brasil). Belo Horizonte , SP, Brazil
• Associated research grant: 18/23098-0 - MENTORED: from modeling to experimentation - predicting and detecting DDoS and zero-day attacks, AP.TEM

Abstract

The growing adoption of Internet of Things (IoT) devices has expanded the surface for cyberattacks, making the development of new threat detection approaches essential. This undergraduate research project proposes the integration of Large Language Models (LLMs) into cybersecurity to enhance the identification and potential mitigation of threats in IoT environments. By combining Natural Language Processing (NLP) techniques and machine learning, the study aims to develop models capable of analyzing network traffic and security events to detect anomalous patterns indicative of cyber threats. This research will contribute to innovation in the field of cybersecurity by demonstrating the feasibility of using LLMs as an effective tool for defending IoT environments.