An auctioning reputation system based on anomaly

Existing reputation systems used by online auction houses do not address the concern of a buyer shopping for commodities—finding a good bargain. These systems do not provide information on the practices adopted by sellers to ensure profitable auctions. These practices may be legitimate, like imposing a minimum starting bid on an auction, or fraudulent, like using colluding bidders to inflate the final price in a practice known as shilling. We develop a reputation system to help buyers identify sellers whose auctions seem price-inflated. Our reputation system is based upon models that characterize sellers according to statistical metrics related to price inflation. We combine the statistical models with anomaly detection techniques to identify the set of suspicious sellers. The output of our reputation system is a set of values for each seller representing the confidence with which the system can say that the auctions of the seller are price-inflated. We evaluate our reputati...

• Type: Conference
• Year: 2005
• Where: CCS
• Authors: Shai Rubin, Mihai Christodorescu, Vinod Ganapathy, Jonathon T. Giffin, Louis Kruger, Hao Wang, Nicholas Kidd
• Keywords: Auctions, Buyers Identify Sellers, CCS 2005, Reputation System, Security Privacy