Machine learning technique for phishing website detection

• Main Authors: Nurul Amira, Mohd Zin, Mohd Faizal, Ab Razak, Ahmad Firdaus, Zainal Abidin, Ernawan, Ferda, Nor Saradatul Akmar, Zulkifli
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/40812/1/Machine%20Learning%20Technique%20for%20Phishing%20Website%20Detection.pdf; http://umpir.ump.edu.my/id/eprint/40812/2/machine%20learning%20technique%20for%20phishing%20website.pdf; http://umpir.ump.edu.my/id/eprint/40812/; https://doi.org/10.1109/ICSECS58457.2023.10256280

The Internet has emerged as an indispensable tool in both our personal and professional life in our modern day. As a direct consequence of this, the number of customers who make their purchases over the Internet is quickly increasing. Internet users may be vulnerable to a wide variety of web threats because of this fact. These threats may result in monetary loss, fraudulent use of credit cards, loss of personal data, potential damage to a brand's reputation, and customer mistrust in e-commerce and online banking. Phishing is a sort of cyber threat that may be defined as the practice of imitating a genuine website for the purpose of stealing sensitive information such as usernames, passwords, and credit card numbers. This research focuses on strategies for detecting phishing attacks. This study apply a machine learning approach to detect a phishing attack. As a result, this study able to detect phishing with accuracy 94%.