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Reseach Article

E-Auction Frauds - A survey

by V M Noufidali, Jobin S Thomas, Felix Arokya Jose
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 61 - Number 14
Year of Publication: 2013
Authors: V M Noufidali, Jobin S Thomas, Felix Arokya Jose
10.5120/10000-4863

V M Noufidali, Jobin S Thomas, Felix Arokya Jose . E-Auction Frauds - A survey. International Journal of Computer Applications. 61, 14 ( January 2013), 41-45. DOI=10.5120/10000-4863

@article{ 10.5120/10000-4863,
author = { V M Noufidali, Jobin S Thomas, Felix Arokya Jose },
title = { E-Auction Frauds - A survey },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 61 },
number = { 14 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 41-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume61/number14/10000-4863/ },
doi = { 10.5120/10000-4863 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:09:09.426985+05:30
%A V M Noufidali
%A Jobin S Thomas
%A Felix Arokya Jose
%T E-Auction Frauds - A survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 61
%N 14
%P 41-45
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The current business arena shows unimaginable augmentation through applications providing all sorts of electronic customer services. One major proliferation was the overture of online auctions enabling the customer community to bid for and purchase large variety of goods. The nature of Internet auctions is high degree of anonymity, number of legal opportunities to buy and sell, and low costs for entry and exit, etc. . . , fraudsters can easily establish frauds in auction activities. Clear fact is that information asymmetry between sellers and buyers and lacking of immediately examining authenticity of the merchandise, the buyer can't verify the seller and the characteristics of the merchandise until after the transaction is completed. This paper classifies the different e-auction frauds and its uncovering methods, doing a detailed analysis based on available bidding trends.

References
  1. Michel J. A Berry Gordon S. Linoff,"Data Mining Techniques" Second edition WILEY Publication.
  2. P. Resnick, K. Kuwabara, R. Zeckhauser, and E. Friedman. "Reputation systems" Communications of the ACM, 43(12),2000.
  3. J. Han and M. Kamber, "Data Mining: Concepts and Techniques", Morgan Kaufmann Publishers, 2001.
  4. P. Resnick and R. Zeckhauser. "Trust among strangers in Internet transactions: Empirical analysis of eBay's reputation system".
  5. In M. R. Baye, editor, The Economics of the Internet and E-Commerce, volume 11 of Advances in Applied Microeconomics. Elsevier Science, Amsterdam, Netherlands,2002.
  6. Pereira, A. , Lago, A Maranzato, R. and Neubert, M. "Fraud detection in reputation systems in e-markets using logistic regression. " In Proceedings of the 2010 ACM Symposium on Applied Computing, Sierre, Switzerland, March 22–26, 2010, ACM Press, New York, NY, 2010, 14–26.
  7. Wang, J. , and Chiu, C. Q. "Detecting online auction inflated-reputation behaviours using social network analysis". In Proceedings of North American Association for Computational Social and Organizational Science 2005, Notre Dame, Indiana, June 26–28, 2005.
  8. Rubin, S. , Christodorescu, M. , Ganapathy, V. , Giffin, J. T. , Louis Kruger, L. , Wang, H. ,and Kidd, N. "An auctioning reputation system based on anomaly". In Proceedings of the 12th ACM Conference on Computer and Communications Security, Alexandria, VA, November 7–10, 2005, ACM Press, New York, NY, 2005.
  9. Pandit, S. , Chau, D. H. , Wang, S. , and Faloutsos, C. NetProbe: "A fast and scalable system for fraud detection in online auction networks". In Proceedings of the 16th international Conference on the World Wide Web, Banff, Canada, May 8–12, 2007,201–210.
  10. Shai Rubin, Mihai,Christodorescu,Vinod Ganapathy, Jonathon T. Giffin Louis Kruger Hao Wang:"Auctioning Reputation System Based on Anomaly Detection" Computer Sciences Department University of Wisconsin, Madison
  11. Roberto Marmo "Data Mining for Fraud Detection System" University of Pavia, Italy.
  12. Kenneth A. Frank "Mapping interactions within and between cohesive subgroups" Michigan State University, Department of Counselling, Educational Psychology and Special Education, East Lansing, M148824-1034, USA
  13. Borgatti, P. "What Is Social Network Analysis?" 1998. 1998 Social Networks Conference in Barcelona, 5-21
  14. Freeman, L. C. "Centrality in Social Network: I. Conceptual Clarification," Social Networks (1) 1979.
  15. H. Goldberg and R. Wong (1998). "Restructuring Transactional Data for Link Analysis in the FinCEN AI System. "AAAI Technical Report FS-98-01,www. aaai. org.
  16. NW3C. National white collar crime and the Federal Bureau Investigation: 2009 Internet crime report – January 1–December
  17. IC3 annual report about frauds www. ic3. gov/media/annualreport/2011_IC3Report. pdf.
  18. Chau, P. "Catching bad guys with graph mining". XRDS: Crossroads, The ACM Magazine for Students 17, 3, 2011.
  19. Gavish, B. , and Tucci, C. "Reducing Internet auction fraud". Communications of the ACM, 51, 5, 2008, 89–97.
  20. eBay Inc. First quarter 2005 financial results, April 2005.
  21. Fei Donga, Sol M. Shatza and Haiping Xub "Combating Online In-Auction Fraud: Clues, Techniques andChallenges"
  22. Online auction deal or steal http://www. scambusters. org/Scambusters43. html
Index Terms

Computer Science
Information Sciences

Keywords

Detecting Techniques Auction fraud Data Mining SNA Reputation System