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Proactive Phishing Defense: A URL Classification System Using Machine Learning

Publisher: IEEE

Authors: Jawad Samer, Aliraqia University Alnajjar Satea, Aliraqia University

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Abstract:

Phishing attacks are the most common cyber attacks nowadays. Phishing attacks rely on social engineering concepts. However, URLs are a fulcrum for phishing attacks. A web application is proposed to classify URLs based on the Random Forest model, and results with an accuracy of 98.2% are achieved.

Keywords: Decision trees, Feature extraction, Phishing, Random Forest, URLs.

Published in: 2024 Asian Conference on Communication and Networks (ASIANComNet)

Date of Publication: --

DOI: -

Publisher: IEEE

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