Year: 2025
Type: article
Abstract: —The Internet has become an indispensable part of our life, However, It also has provided opportunities to anony- mously perform malicious activities like Phishing. Phishers try to deceive their victims by social engineering or creating mock- up websites to steal information such as account ID, username, password from individuals and organizations. Although many methods have been proposed to detect phishing websites, Phishers have evolved their methods to escape from these detection methods. One of the most successful methods for detecting these malicious activities is Machine Learning. This is because most Phishing attacks have some common characteristics which can be identified by machine learning methods. In this paper, we compared the results of multiple machine learning methods for predicting phishing websites.
Authors: JAYASURYA S R -, SHARAN T G -, DHANESH RAJ R -
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409395643