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URL Phishing Detection System Utilizing Catboost Machine Learning Approach

The development of various phishing websites enables hackers to access confidential personal or financial data, thus, decreasing the trust in e-business. This paper compared the detection techniques utilizing URL-based features. To analyze and compare the performance of supervised machine learning c...

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Bibliographic Details
Main Authors: Lim, Chian Fang, Ayop, Zakiah, Anawar, Syarulnaziah, Othman, Nur Fadzilah, Harum, Norharyati, Abdullah, Raihana Syahirah
Format: Article
Language:English
Published: International Journal of Computer Science and Network Security (IJCSNS) 2021
Online Access:http://eprints.utem.edu.my/id/eprint/25543/2/2.3.1.1.1%20IJCSNS%20URL%20PHISHING%20UTILIZING%20CATBOOST%20MACHINE%20LEARNING%20APPROACH.PDF
http://eprints.utem.edu.my/id/eprint/25543/
http://paper.ijcsns.org/07_book/202109/20210939.pdf
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http://eprints.utem.edu.my/id/eprint/25543/2/2.3.1.1.1%20IJCSNS%20URL%20PHISHING%20UTILIZING%20CATBOOST%20MACHINE%20LEARNING%20APPROACH.PDF
http://eprints.utem.edu.my/id/eprint/25543/
http://paper.ijcsns.org/07_book/202109/20210939.pdf

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