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Phishing e mail detection in e Banking using data mining techniques

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dc.contributor.author Hanees, A. L.
dc.date.accessioned 2020-01-09T03:56:38Z
dc.date.available 2020-01-09T03:56:38Z
dc.date.issued 2019-12-18
dc.identifier.citation 8th South Eastern University International Arts Research Symposium -2019. 18th December 2019. South Eastern University of Sri Lanka, Oluvil, Sri Lanka. pp. 104. en_US
dc.identifier.isbn 978-955-627-203-1
dc.identifier.uri http://ir.lib.seu.ac.lk/handle/123456789/4257
dc.description.abstract Phishing is a type of social engineering attack often used to steal user data. Especially in e-banking attackers sent an email that appears legitimate but is actually meant to lure a potential victim into providing some level of personal information for nefarious purpose, including login credentials and credit card numbers. In this paper we employ four data mining classification algorithms to detect the phishing emails in e-banking and then we use the weighted majority vote ensemble method to improve the detection of phishing emails and compare the performance of each. Experimental results shows that decision tree builds the best classifier. en_US
dc.language.iso en_US en_US
dc.publisher Faculty of Arts and Culture South Eastern University of Sri Lanka. en_US
dc.subject Phishing emails en_US
dc.subject E-Banking en_US
dc.subject Ensemble en_US
dc.subject Weighted majority vote en_US
dc.subject Data mining algorithm en_US
dc.title Phishing e mail detection in e Banking using data mining techniques en_US
dc.type Article en_US


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  • SEUIARS - 2019 [127]
    South Eastern University International Arts Research Symposium -2019

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