Abstract
Internet auction fraud has become prevalent. Methodologies for detecting fraudulent transactions use historical information about Internet auction participants to decide whether or not a user is a potential fraudster. The information includes reputation scores, values of items, time frames of various activities and transaction records. This paper presents a distinctive set of fraudster characteristics based on an analysis of 278 allegations about the sale of counterfeit goods at Internet auction sites. Also, it applies a Bayesian approach to analyze the relevance of evidence in Internet auction fraud cases.
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M. Chae, S. Shim, H. Cho and B. Lee, Empirical analysis of online auction fraud: Credit card phantom transactions, Expert Systems with Applications, vol. 37(4), pp. 2991–2999, 2010.
China Internet Network Information Center, Statistical Survey Report on Internet Development in China (Abridged Edition), Beijing, China (www.cnnic.net.cn/uploadfiles/pdf/2008/8/15/145744.pdf), 2008.
R. Choo, Organized crime groups in cyberspace: A typology, Trends in Organized Crime, vol. 11(3), pp. 270–295, 2008.
C. Chua and J. Wareham, Self-regulation for online auctions: An analysis, Proceedings of the Twenty-Third International Conference on Information Systems, pp. 115–125, 2002.
Data Center of the China Internet, The First Half of 2008 China Internet User Measurement Data IUI Index Report, Beijing, China, 2008.
I. Evett, Establishing the evidential value of a small quantity of material found at a crime scene, Journal of the Forensic Science Society, vol. 33(2), pp. 83–86, 1993.
S. Gajek and A. Sadeghi, A forensic framework for tracing phishers, Proceedings of the Third International Conference on the Future of Identity in the Information Society, pp. 19–33, 2008.
D. Gregg and J. Scott, A typology of complaints about eBay sellers, Communications of the ACM, vol. 51(4), pp. 69–74, 2008.
Internet Crime Complaint Center, 2008 Internet Crime Report, National White Collar Crime Center, Richmond, Virginia, 2008.
J. Keppens, Towards qualitative approaches to Bayesian evidential reasoning, Proceedings of the Eleventh International Conference on Artificial Intelligence and Law, pp. 17–25, 2007.
M. Kobayashi and T. Ito, A transactional relationship visualization system in Internet auctions, Studies in Computational Intelligence, vol. 110, pp. 87–99, 2008.
Y. Ku, Y. Chen and C. Chiu, A proposed data mining approach for Internet auction fraud detection, Proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics, pp. 238–243, 2007.
M. Kwan, K. Chow, F. Law and P. Lai, Reasoning about evidence using Bayesian networks, in Advances in Digital Forensics IV, I. Ray and S. Shenoi (Eds.), Springer, Boston, Massachusetts, pp. 275–289, 2008.
D. Lucy, Introduction to Statistics for Forensic Scientists, Wiley, Chichester, United Kingdom, 2005.
M. Morzy, New algorithms for mining the reputation of participants of online auctions, Algorithmica, vol. 52(1), pp. 95–112, 2008.
K. Ochaeta, Fraud Detection for Internet Auctions: A Data Mining Approach, Ph.D. Thesis, College of Technology Management, National Tsing-Hua University, Hsinchu, Taiwan, 2008.
R. Overill, M. Kwan, K. Chow, P. Lai and F. Law, A cost-effective model for digital forensic investigations, in Advances in Digital Forensics V, G. Peterson and S. Shenoi (Eds.), Springer, Heidelberg, Germany, pp. 231–240, 2009.
Y. Sakurai and M. Yokoo, A false-name-proof double auction protocol for arbitrary evaluation values, Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 329–336, 2003.
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Kwan, M. et al. (2010). Evaluation of Evidence in Internet Auction Fraud Investigations. In: Chow, KP., Shenoi, S. (eds) Advances in Digital Forensics VI. DigitalForensics 2010. IFIP Advances in Information and Communication Technology, vol 337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15506-2_9
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DOI: https://doi.org/10.1007/978-3-642-15506-2_9
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