Computer Sciences Dept.

Computer Security and Cryptography Seminar:
November 2005 Events

Date &
Location
Event
Monday, November 7, 2005
4:00 - 5:00 PM
2310 CS
Shai Rubin (web)
Department of Computer Sciences, University of Wisconsin, Madison (web)
An Auctioning Reputation System Based on Anomaly Detection

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 auc- tions 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 tech- niques to identify the set of suspicious sellers. The output of our reputa- tion 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 reputation system on 604 high-volume sellers who posted 37,525 auctions on eBay. Our system automatically pinpoints sellers whose auctions contain potential shill bidders. When we manually analyze these sellers' auctions, we find that many winning bids are at about the items' market values, thus undercutting a buyer's ability to find a bargain and demonstrating the effectiveness of our reputation system.

Conference practice talk.

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Created and maintained by Mihai Christodorescu (http://www.cs.wisc.edu/~mihai)
Created: Fri Jul 29 11:34:22 2005
Last modified: Fri Jul 29 11:35:25 Central Daylight Time 2005
 
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