Detecting Fraud in Internet Auction Systems

  • Yanlin Peng
  • Linfeng Zhang
  • Yong Guan
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 306)


Fraud compromises the thriving Internet auction market. Studies have shown that fraudsters often manipulate their reputations through sophisticated collusions with accomplices, enabling them to defeat the reputation-based feedback systems that are used to combat fraud. This paper presents an algorithm that can identify colluding fraudsters in real time. Experiments with eBay transaction data show that the algorithm has low false negative and false positive rates. Furthermore, the algorithm can identify fraudsters who are innocent at the time of the data collection, but engage in fraudulent transactions soon after they accumulate good feedback ratings.


Internet auctions fraud detection 


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Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Yanlin Peng
  • Linfeng Zhang
  • Yong Guan

There are no affiliations available

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