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Prevention of Phishing Attacks Based on Discriminative Key Point Features of WebPages
Mallikka Rajalingam, Salah Ali Alomari, Putra Sumari
Pages - 1 - 18     |    Revised - 15-01-2012     |    Published - 21-02-2012
Volume - 6   Issue - 1    |    Publication Date - February 2012  Table of Contents
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KEYWORDS
Image Clustering and Retrieval, Anti-Phishing mechanism, Digital Image Processing, Security, CCH
ABSTRACT
Phishing is the combination of social engineering and technical exploits designed to convince a victim to provide personal information, usually for the monetary gain of the attacker (Phisher). Attempts to stop phishing by preventing a user from interacting with a malicious web site have shown to be ineffective. In this paper, present an effective image-based anti-phishing scheme based on discriminative key point features in WebPages. We use an invariant content descriptor, the Contrast Context Histogram (CCH), to compute the similarity degree between suspicious pages and authentic pages. To determine whether two images are similar, a common approach involves extracting a vector of salient features from each image, and computing the distance between the vectors, which is taken as the degree of visual difference between the two images. The results show that the proposed scheme achieves high accuracy and low error rates.
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Miss Mallikka Rajalingam
Universiti Sains malaysia - Malaysia
mallikka2002@yahoo.com
Mr. Salah Ali Alomari
Universiti Sains malaysia - Malaysia
Associate Professor Putra Sumari
Universiti Sains malaysia - Malaysia