Feature-based phishing detection technique

Xin, Mei Choo and Kang, Leng Chiew and Dayang Hanani, Abang Ibrahim and Nadianatra, Musa and San, Nah Sze and Wei, King Tiong (2016) Feature-based phishing detection technique. Journal of Theoretical and Applied Information Technology, 91 (1). pp. 101-106. ISSN 1992-8645

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Abstract

Phishing is an Internet fraud to entice unsuspecting victims. The tactic of phishing is to impersonate the trusted entities by employing both social engineering and technical subterfuge. Moreover, phishing is a form of online identity theft that creates a fake copy of popular site. There are many types of anti-phishing techniques available. However, they are mostly still in the infancy stage which may give false alarm to the user. Therefore, this research aims to develop a feature-based phishing detection technique to overcome the limitation. The proposed method involves aggregating new features with several existing features to form a sensitive features set. Based on the features set, the proposed method will utilise support vector machine to perform the classification. The experimental results show convincing performance with 95.33 percent of accuracy.

Item Type: Article
Uncontrolled Keywords: URL Features, Website Features, Phishing Detection, Anti-Phishing, Feature Extraction, Classification, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Ibrahim
Date Deposited: 17 Oct 2016 01:45
Last Modified: 17 Feb 2017 01:47
URI: http://ir.unimas.my/id/eprint/13943

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