Harnessing evolving machine learning techniques for enhanced intrusion detection system

Sonavadia, Viral Sharad (2024) Harnessing evolving machine learning techniques for enhanced intrusion detection system. Masters thesis, Dublin, National College of Ireland.

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Abstract

The overall design specification section determines the functional portion of the data execution proportion. This determines the functional evaluation of all the constructional approaches. The designing approach determines the involvement of Python coding. The designing approach introduces the functional section of the configuration of IDS. The implementation defines the introduction of the evaluation process by using data reading functionality. The supportable execution also provides the designing of the executional parameters. The evaluation defines the construction of various machine learning models such as KNN, SVM, Random Forest, Decision Tree, and ANN. The evaluation of those models supports the finding of the most suitable model for the detection of intrusion in the network. Future development supports the upgradation of this research process by the implementation of AI techniques and advanced methods.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Heffernan, Niall UNSPECIFIED
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 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:	31 Jul 2025 11:23
Last Modified:	31 Jul 2025 11:23
URI:	https://norma.ncirl.ie/id/eprint/8375

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