Inference of Online Auction Shills Using Dempster-Shafer Theory

We present a shilling behavior detection and verification approach for online auction systems. Assuming a model checking technique to detect shill suspects in real-time, we focus on how to verify shill suspects using Dempster-Shafer theory of evidence. To demonstrate the feasibility of our approach,...

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Bibliographic Details
Published in2009 Sixth International Conference on Information Technology: New Generations pp. 908 - 914
Main Authors Fei Dong, Shatz, S.M., Haiping Xu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2009
Subjects
auction fraud
Computer science
Data analysis
Data mining
Data security
Dempster-Shafer theory
Information science
Information technology
online auctions
Pattern matching
Quality of service
Shill bidding
shill verification
Testing
Uncertainty
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ISBN1424437709
9781424437702
DOI10.1109/ITNG.2009.28

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Summary:We present a shilling behavior detection and verification approach for online auction systems. Assuming a model checking technique to detect shill suspects in real-time, we focus on how to verify shill suspects using Dempster-Shafer theory of evidence. To demonstrate the feasibility of our approach, we provide a case study using real eBay auction data. The analysis results show that our approach can detect shills and that using Dempster-Shafer theory to combine multiple sources of evidence of shilling behavior can reduce the number of false positive results that would be generated from a single source of evidence.
ISBN:1424437709
9781424437702
DOI:10.1109/ITNG.2009.28