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Using feature selection and classification scheme for automating phishing email detection

A. Hamid, Isredza Rahmi and Abawajy, Jemal and Kim, Tai-hoon (2013) Using feature selection and classification scheme for automating phishing email detection. Studies in informatics and control, 22 (1). pp. 61-70. ISSN 12201766

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Email has become the critical communication medium for most organizations. Unfortunately, email-born attacks in computer networks are causing considerable economic losses worldwide. Exiting phishing email blocking appliances have little effect in weeding out the vast majority of phishing emails. At the same time, online criminals are becoming more dangerous and sophisticated. Phishing emails are more active than ever before and putting the average computer user and organizations at risk of significant data, brand and financial loss. In this paper, we propose a hybrid feature selection approach based combination of content-based and behaviour-based. The approach could mine the attacker behaviour based on email header. On a publicly available test corpus, our hybrid features selection is able to achieve 94% accuracy rate.

Item Type: Article
Uncontrolled Keywords: Internet security; behavior-based; feature selection; phishing
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Information Security
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 13 Aug 2018 03:21
Last Modified: 31 Oct 2019 02:33
URI: http://eprints.uthm.edu.my/id/eprint/9788
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