ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774


DETECTION OF PHISHING WEBSITES USING EXTREME LEARNING MACHINE BASED ON URL

Abstract

Abstract- Phishing is one kind of cyberattack and at the same time, it is most dangerous and common attack to acquirepersonal information, account details, organizational details, credit carddetails or password of a user to conduct transactions. Phishing websites looksimilar to the appropriate ones which is difficult to differentiate betweenthem. The motive of this study is to perform Extreme Learning Machine(ELM)based on different 30 features classification using Machine Learning approach.Most of the phishing URL’s use HTTPS to avoid getting detected. There are threeapproaches for detection of phishing websites. The first approach analyzingdifferent features of URL, second approach checking legitimacy of website andknowing where the website is hosted or not and it also check who are managingit, third approach checking genuineness of website.

Keywords—Phishing, ExtremeLearning Machine, Features Classification, URL, Information Security.


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Paper Submission Open For October 2024
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Last date for paper submission 30th October, 2024
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Publication of Paper Within 15-30 Days after completing all the formalities
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