Leveraging Advanced Machine Learning Ensembles for Enhanced IoT Security: A Comprehensive Study on Intrusion Detection Systems

Balankhe, Kshiteej Avinash (2024) Leveraging Advanced Machine Learning Ensembles for Enhanced IoT Security: A Comprehensive Study on Intrusion Detection Systems. Masters thesis, Dublin, National College of Ireland.

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Abstract

The Internet of Things (IoT) for instance, has significantly changed the way devices communicate and how automation is facilitated across large ecosystems efficiently in a connected manner. This has a massively increased the attack surface, making secure policies and tools like Intrusion Detection Systems (IDS) absolutely critical for protecting them. This research focuses on the use of state-of-the-art machine learning algorithms Logistic Regression, Decision Tree and LightGBM, to design an IDS capable for usage in IoT networks. We then demonstrate that using the BoT-IoT dataset as a training and testing data, modelling the semi-supervised SW under ensemble learning principles enhances detection performance compared to individual models. This indicates that current machine learning techniques have the capability to improve IoT security mechanisms mainly through their powerful, complex adaptability features of typical dynamic and smart nature challenges in designing secure environments for IoT.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Aleburu, Joel UNSPECIFIED
Uncontrolled Keywords:	IoT; Intrusion Detection System; Machine Learning; Logistic Regression; Decision Trees; LightGBM; Stacking Ensemble; BoT-IoT dataset
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > Computer networks > Internet of things Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	29 Jul 2025 10:29
Last Modified:	29 Jul 2025 10:29
URI:	https://norma.ncirl.ie/id/eprint/8294

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