URL Phishing Detection System Utilizing Catboost Machine Learning Approach

• 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
• Institution: Universiti Teknikal Malaysia Melaka

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...