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Issue No.10 - October (2009 vol.42)
pp: 78-86
Ahmed Abbasi , University of Wisconsin-Milwaukee
Hsinchun Chen , University of Arizona
As fake website developers become more innovative, so too must the tools used to protect Internet users. A proposed system combines a support vector machine classifier and a rich feature set derived from website text, linkage, and images to better detect fraudulent sites.
machine learning, artificial Intelligence, computing methodologies, Web text analysis, natural language processing, computer systems organization
Ahmed Abbasi, Hsinchun Chen, "A Comparison of Tools for Detecting Fake Websites", Computer, vol.42, no. 10, pp. 78-86, October 2009, doi:10.1109/MC.2009.306
1. C.E.H. Chua and J. Wareham, "Fighting Internet Auction Fraud: An Assessment and Proposal," Computer, Oct. 2004, pp. 31-37.
2. Z. Gyongyi and H. Garcia-Molina, "Spam: It's Not Just for Inboxes Anymore," Computer, Oct. 2005, pp. 28-34.
3. B. Wu and B.D. Davison, "Identifying Link Farm Spam Pages," Proc. 14th Int'l Conf. World Wide Web (WWW 05), ACM Press, 2005, pp. 820-829.
4. A. Ntoulas et al., "Detecting Spam Web Pages through Content Analysis," Proc. 15th Int'l Conf. World Wide Web (WWW 06), ACM Press, 2006, pp. 83-92.
5. A. Abbasi and H. Chen, "Detecting Fake Escrow Websites Using Rich Fraud Cues and Kernel-Based Methods," Proc. Workshop on Information Technologies and Systems (WITS 07), WITS, 2007, pp. 55-60.
6. N. Chou et al., "Client-Side Defense against Web-Based Identity Theft," Proc. 11th Ann. Network and Distributed System Security Symp. (NDSS 04), Internet Society, 2004.
7. W. Liu et al., "An Antiphishing Strategy Based on Visual Similarity Assessment," IEEE Internet Computing, Mar./Apr. 2006, pp. 58-65.
8. I. MacInnes, D. Musgrave, and J. Laska, "Electronic Commerce Fraud: Towards an Understanding of the Phenomenon," Proc. Hawaii Int'l Conf. Systems Sciences (HICSS 05), IEEE CS Press, 2005, pp. 181.1-181.11.
9. E. Levy, "Criminals Become Tech Savvy," IEEE Security and Privacy, Mar./Apr. 2004, pp. 65-68.
10. Y. Zhang et al., "Phinding Phish: Evaluating Anti-Phishing Tools," Proc. 14th Ann. Network and Distributed System Security Symp. (NDSS 07), Internet Society, 2007.
11. L. Li and M. Helenius, "Usability Evaluation of Anti-Phishing Toolbars," J. Computer Virology, vol. 3, no. 2, 2007, pp. 163-184.
12. P. Hariharan, F. Asgharpour, and L.J. Camp, "NetTrust—Recommendation System for Embedding Trust in a Virtual Realm," Proc. ACM Conf. Recommender Systems (RecSys 07), ACM Press, 2007.
13. M. Wu, R.C. Miller, and S.L. Garfinkel, "Do Security Toolbars Actually Prevent Phishing Attacks?," Proc. Conf. Human Factors in Computing Systems (CHI 06), ACM Press, 2006, pp. 601-610.
14. M. Diligenti et al., "Focused Crawling Using Context Graphs," Proc. 26th Conf. Very Large Databases (VLDB 2000), Morgan Kaufmann, 2000, pp. 527-534.
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