Machine Learning Driven Network Protection in Cloud Computing Environments

Hiregowja Kumara, Siddesh (2023) Machine Learning Driven Network Protection in Cloud Computing Environments. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (1MB) | Preview
Preview	PDF (Configuration Manual) Download (2MB) | Preview

Abstract

In the rapidly evolving landscape of cloud computing, the protection of network infrastructure has become a paramount concern. This study delves into the realm of Hybrid Deep Learning-Driven Network Protection within Cloud Computing Environments, leveraging advanced methodologies and models to fortify security measures. The primary goal is to develop robust intrusion detection systems capable of discerning between normal network behaviour and potential threats. The methodology used in this study entails the use of multiple deep learning models, including LSTM ( Long Short-Term Memory), BiLSTM (Bidirectional Long ShortTerm Memory), and BiLSTM with an attention mechanism. These models are meticulously trained and tested using the KddCup’99 dataset, a benchmark in the field of intrusion detection. The process includes data preprocessing, model training, hyperparameter tuning, and evaluation using metrics like accuracy, precision, recall, and F1-score. The results of this study reveal that the BiLSTM model with an attention mechanism emerges as the most effective solution, achieving an exceptional accuracy of 99%. This model showcases superior performance in accurately identifying network intrusions while maintaining high precision and recall, making it a compelling choice for network protection in cloud environments.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Makki, Ahmed 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:	28 Mar 2025 11:39
Last Modified:	25 Apr 2025 10:08
URI:	https://norma.ncirl.ie/id/eprint/7346

Actions (login required)

View Item