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Rajendra Subbu, Prajesh Nikhil (2024) A Comparative Analysis of Hybrid Machine Learning Techniques for Network Intrusion Detection in Cloud Environments. Masters thesis, Dublin, National College of Ireland.
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Abstract
Network Intrusion Detection Systems (NIDS) within cloud environments by using and comparing machine learning algorithms. Due to the increasing number of cyber threats, there is a need to safeguard critical data in cloud environments. The existing methods such as NIDS, in particular traditional signature-based NIDS, are becoming less and less effective against advanced threats like polymorphic malware and zero-day attacks. Previous work raised attention to the problems of these conventional strategies and suggested replacements such as advanced machine learning methods and anomaly-based detection. By developing a hybrid NIDS model that combines Random Forest (RF) classifiers and Long Short-Term Memory (LSTM) networks, this study fills in these gaps. this study explores the diverse machine learning technologies using deep learning to determine an efficient and highly accurate model to detect intruders in cloud environments. The goal of this research is to develop a strong and effective network intrusion detection system (NIDS) that can navigate the intricacies of cloud environments and offer superior defense against cyber threats by utilizing the extensive UNSW-NB15 dataset. The main goal is to develop an advanced NIDS model capable of navigating cloud complexities and give a valuable enhanced model to stakeholders to help defend against cyber threats by achieving high accuracy using hybrid models and with comparison with the other Machine learning model which can lead to the development of more robust NIDS in cloud environments.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Kazmi, Aqeel UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing 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 Cloud Computing |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 04 Jul 2025 10:31 |
| Last Modified: | 04 Jul 2025 10:31 |
| URI: | https://norma.ncirl.ie/id/eprint/8050 |
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