Leveraging Large Language Models for Enhanced Intrusion Detection Systems: A Novel Approach to Anomaly Detection and Threat Intelligence

The subject explores the application of Large Language Models (LLMs) to enhance Intrusion Detection Systems (IDS). With the rapid evolution of cyber threats, traditional IDS methods struggle to adapt to new and sophisticated attack patterns. This research aims to integrate LLMs' advanced pattern recognition, contextual understanding, and language processing capabilities to improve anomaly detection and threat intelligence. 

Through a novel approach, the research explores anomaly detection at multiple levels, from network traffic to user behavior, offering a scalable, adaptive IDS solution. Expected outcomes include higher detection accuracy, reduced false positives, and an enriched understanding of cybersecurity threats, paving the way for more intelligent, adaptable IDS frameworks.

Large Language Models, Intrusion detection, Anomaly detection, Threat Intelligence, Cyber-attack

Educational Background:

Master's/Engineering degree in Computer Science, Artificial Intelligence, Cybersecurity, Data Science, or a related field. This ensures foundational knowledge in both machine learning and cybersecurity.

Knowledge in Machine Learning and NLP

- Strong understanding of machine learning and deep learning fundamentals (eg, neural networks, optimization, classification). 

- Familiarity with natural language processing (NLP) concepts and models, especially Large Language Models (LLMs) such as BERT, GPT, or similar Architectures.

Knowledge in Cybersecurity:

- Knowledge of intrusion detection systems (IDS), network protocols, and common cybersecurity threats.

Programming and Technical Skills:

- Proficiency in Python (or similar language) with experience in frameworks like TensorFlow for implementing and fine-tuning deep learning models.

- Familiarity with cybersecurity tools and network analysis platforms (eg, Wireshark, Snort)

November 11, 2024

Please send your application to: Cedoc.admission@ueuromed.org & t.aittchakoucht@ueuromed.org

Prof. Taha AIT TCHAKOUCHT