Intelligent Anomaly Detection in Network Traffic using Advanced Machine Learning Techniques

-, Shaik Junaid (2025) Intelligent Anomaly Detection in Network Traffic using Advanced Machine Learning Techniques. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (1MB) | Preview
Preview	PDF (Configuration Manual) Download (572kB) | Preview

Abstract

This research aims to determine how emerging ML algorithms and techniques increase the efficiency and accuracy of anomaly detection in network traffic to enhance cybersecurity measures. This research seeks to assess the efficiency, sustainability and overall performance of different supervised and unsupervised ML techniques in real-world contexts with imbalanced data and computational constraints.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Thomas, Lavish UNSPECIFIED
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Artificial Intelligence
Depositing User:	Ciara O'Brien
Date Deposited:	11 Aug 2026 14:21
Last Modified:	11 Aug 2026 14:21
URI:	https://norma.ncirl.ie/id/eprint/9490

Actions (login required)

View Item