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Intelligent phishing website detection system using fuzzy techniques

Aburrous, Maher R.
Hossain, M. Alamgir
Thabatah, F.
Dahal, Keshav P.
Publication Date
2008
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Copyright © [2008] IEEE. Reprinted from the Proceedings of the International Conference on Information & Communication Technologies: From Theory to Applications (ICCTA'08). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bradford's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubspermissions@ ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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Abstract
Phishing websites are forged web pages that are created by malicious people to mimic web pages of real websites and it attempts to defraud people of their personal information. Detecting and identifying Phishing websites is really a complex and dynamic problem involving many factors and criteria, and because of the subjective considerations and the ambiguities involved in the detection, Fuzzy Logic model can be an effective tool in assessing and identifying phishing websites than any other traditional tool since it offers a more natural way of dealing with quality factors rather than exact values. In this paper, we present novel approach to overcome the `fuzziness¿ in traditional website phishing risk assessment and propose an intelligent resilient and effective model for detecting phishing websites. The proposed model is based on FL operators which is used to characterize the website phishing factors and indicators as fuzzy variables and produces six measures and criteria¿s of website phishing attack dimensions with a layer structure. Our experimental results showed the significance and importance of the phishing website criteria (URL & Domain Identity) represented by layer one, and the variety influence of the phishing characteristic layers on the final phishing website rate.
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Published version
Citation
Aburrous M, Hossain MA, Thabatah F et al (2008) Intelligent phishing website detection system using fuzzy techniques. In: Proceedings of the 3rd International Conference on Information & Communication Technologies: From Theory to Applications (ICCTA'08). New York: IEEE.
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