Phishing Detection Using MLT

—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.

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Publication Details

Journal
International Journal on Science and Technology
Published
2025-04-13
DOI
https://doi.org/10.71097/ijsat.v16.i2.3400
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Phishing Detection Using MLT

S Jayasurya, Tanya Sharan, D. R.
International Journal on Science and Technology
Spam and Phishing Detection
article

Phishing Detection Using MLT

S Jayasurya, Tanya Sharan, D. R.
article en

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.

International Journal on Science and TechnologyVol. 16(2)
Openalex Percentile: Top 91%
Spam and Phishing Detection
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