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Vol. 4, Sept  Issue  Paper Submission  Deadline : 20th  December 2019...

Vol. 4,  Special Issue(Bi-yearly) -  Paper Submission  Deadline: 20th  December 2019


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SURVEYON: DETECTION OF PHISHING WEBSITES USING EXTREME LEARNING MACHINE BASED ON URL

Abstract

ABSTRACT: Phishing is one kind of cyber attack and at the same time, it is most dangerous and common attack to acquire
personal information, account details, organizational details, credit card details or password of a user to conduct
transactions. Phishing websites look similar to the appropriate ones which is difficult to differentiate between them. 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 three approaches
for detection of phishing websites. The first approach analyzing different features of URL, second approach checking
legitimacy of website and knowing where the website is hosted or not and it also check who are managing it, third approach
checking genuineness of website.
Keywords—Phishing, Extreme Learning Machine, Features Classification, URL, Information Security.

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IMPACT FACTOR: 5.909(2018)

IMPACT FACTOR: 4.109(2017)
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Organized  National Conference on  SUSTAINABLE SOLID WASTE MANAGEMENT (SSWM)

@ AMITY SCHOOL OF ENGINEERING & TECHNOLOGY

Department of Civil Engineering,

Amity University Haryana,


&

  CSEEEC-2019       

  National Computer Science ,Electronics, Electrical  Engineering Conference 



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