Comparative analysis on different phishing website detection techniques
Department of Computer Science and Engineering, COEP Technological University, Pune, India.
Research Article
International Journal of Frontiers in Engineering and Technology Research, 2025, 08(02), 055-062.
Article DOI: 10.53294/ijfetr.2025.8.2.0036
Publication history:
Received on 04 May 2025; revised on 14 June 2025; accepted on 16 June 2025
Abstract:
Phishing attack is an attempt to obtain confidential information or data, such as credit and debit card details, username, passwords, etc. by creating a fake website which is very much similar to genuine website. Because of visual similarity of website, users are not able to distinguish between a legitimate and phishing websites. Phishing attack often targets users to enter their personal information at a phishing website. Then that information is directly send to attackers. In today’s world most of the phishing attack takes place with the help of spoofed emails. The attackers first send the email to victim which looks like it’s come from genuine sender. The spoofed email contains the link to such phishing websites. When the victim clicks this link and enters the credentials and information, the information is directly passed on to the attackers. The attackers then misuse this information. Phishing attack is still among the top ten cyber-attacks. Hence, the security experts are looking for a reliable and steady detection mechanism with high accuracy. This paper aims to compare all the phishing website detection techniques.
Keywords:
Phishing Attack; Phishing Website; Machine Learning Algorithm; Social Engineering; Deep Learning Algorithms; Neural Network
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Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0