Anomaly Detection Method for OT/ICS Environment Using Ensemble Learning

Sayyed, Shifan Anwar (2024) Anomaly Detection Method for OT/ICS Environment Using Ensemble Learning. Masters thesis, Dublin, National College of Ireland.

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Abstract

In this research work we have looked into the current state of OT/ICS security, how important OT/ICS infrastructures are, what is their operational disruption impact and why it is important to secure them. Going forward we have delved into the literature review of relevant research papers, discussing challenges of OT/ICS space and approaches used for securing OT/ICS environment using different types of machine learning algorithms and techniques. This paper proposes an Anomaly Detection method based on ensemble learning model for securing OT/ICS environment. At the end we have discussed the implementation part carried out to develop an anomaly detection system, data transformation and discussion of the result and finally critically analysing the research and discussing the limitation.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Salahuddin, Jawad UNSPECIFIED
Uncontrolled Keywords:	Machine Learning; Supervised Algorithm; Ensemble Learning; Electra Dataset; Operational Technology (OT); Industrial Control Systems (ICS); Cybersecurity
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 08:54
Last Modified:	31 Jul 2025 08:54
URI:	https://norma.ncirl.ie/id/eprint/8368

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