Detection of Phishing URLs using Machine Learning

Varghese, Emin (2024) Detection of Phishing URLs using Machine Learning. Masters thesis, Dublin, National College of Ireland.

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Abstract

Phishing websites are an increasing cybersecurity threat which puts both customers and business at risk as they compromise sensitive data. As phishing acts as the initial step in cyberattacks, early detection of these sites is important. Even though traditional methods, which rely on manual feature engineering are effective, they often find it difficult to catch up with the fishing tactics. This research emphasis on using machine learning (ML) to facilitate and enhance the detection process, improving its adaptability to rising threats. By reviewing URL-based features and training models on a mixed dataset, this study aims to make an innovative system that can easily identify phishing websites and zero-day attacks, improving the security measures and the decreasing the risks related to phishing attacks. PHIUSIIL and Mendeley datasets were preprocessed and then analyzed under six machine learning algorithms. The work also emphasizes the effectiveness of incremental learning solutions, especially for updating data in real-time. This work focuses on the application of machine learning (ML) for the detection of phishing URL. Using PHIUSIIL dataset and Mendeley dataset, a comparative analysis of URLs and content of different models was performed. The results prove the effectiveness of incremental learning strategies and bring focus on the need for strong and easily extendable methods adapted to the current threats.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Moldovan, Arghir Nicolae 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 Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > Electronic Mail T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > Electronic Mail 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:	28 Jul 2025 15:21
Last Modified:	28 Jul 2025 15:21
URI:	https://norma.ncirl.ie/id/eprint/8277

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