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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 3    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 3,March 2012
Mitigating Online Fraud by Ant phishing Model With URL & Image based Webpage Matching
Full Text(PDF, )  PP.6-11  
T.Balamuralikrishna, N.Raghavendrasai, M.Satya Sukumar
Anti-Phishing, Web document analysis, Security, Visual Similarity, Webpage Matching
Phishing is a malicious form of Internet fraud with the aim to steal valuable information such as credit cards, social security numbers, and account information. This is accomplished primarily by crafting a faux online presence to masquerade as a legitimate institution and soliciting information from unsuspecting customers. Phishing is a form of online fraud that aims to steal a user's sensitive information, such as online banking passwords or credit card numbers. The victim is tricked into entering such information on a web page that is crafted by the attacker so that it mimics a legitimate page.
[1] Identity Theft Resource Center, Facts & Statistics, http://www.idtheftcenter.org /facts.shtml.

[2]“Phishing Attack Trends Report, June 2004,” Anti-Phishing Working Group, http://www.antiphishing. org APWG_Phishing_Attack_Report-Jun2004.pdf.

[3]The Anti-Phishing Working Group, “APWG Phishing Trends Reports, [Online] Available: www.antiphishing.org/phishReports Archive.html

[4]P. Robichaux, D.L. Ganger, “Gone Phishing: Evaluating Antiphishing Tools for Windows,” 3Sharp Project Report, Sept. 2006; [Online] Available : www.3sharp.com/ projects/antiphishing/.

[5] L. Wenyin et al., “Detection of Phishing Webpages Based on Visual Similarity,” Proc. World Wide Web Conf. (special interest tracks and posters), A. Ellis and T. Hagino, eds., ACM Press, 2005, pp. 1060–1061.

[6]W. Liu et al., “An Antiphishing Strategy Based on Visual Similarity Assessment”, IEEE Internet Computing, vol. 10, no. 2, 2006, pp. 58–65

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