Understanding phishers' strategies of mimicking uniform resource locators to leverage phishing attacks: A machine learning approach
J. Samantha Tharani, Nalin Asanka Gamagedara Arachchilage

TL;DR
This paper explores how phishers mimic URLs to deceive users, using machine learning to identify key manipulation techniques, which can inform better anti-phishing tools and user education strategies.
Contribution
It uncovers specific URL manipulation techniques used by phishers through feature selection and machine learning, advancing understanding of phishing strategies.
Findings
Identified 10 URL manipulation techniques used by phishers.
Used feature selection methods to analyze 48 URL features.
Results can improve anti-phishing tools and user awareness.
Abstract
Phishing is a type of social engineering attack with an intention to steal user data, including login credentials and credit card numbers, leading to financial losses for both organisations and individuals. It occurs when an attacker, pretending as a trusted entity, lure a victim into click on a link or attachment in an email, or in a text message. Phishing is often launched via email messages or text messages over social networks. Previous research has revealed that phishing attacks can be identified just by looking at URLs. Identifying the techniques which are used by phishers to mimic a phishing URL is rather a challenging issue. At present, we have limited knowledge and understanding of how cybercriminals attempt to mimic URLs with the same look and feel of the legitimate ones, to entice people into clicking links. Therefore, this paper investigates the feature selection of phishing…
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