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.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/2640 |
| Date | January 2008 |
| Creators | Aburrous, Maher R., Hossain, M. Alamgir, Thabatah, F., Dahal, Keshav P. |
| Publisher | IEEE |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Conference paper, Published version |
| Rights | 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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