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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fei Dong Shatz, S.M. Haiping Xu |
| Copyright Year | 2009 |
| Abstract | 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. |
| Starting Page | 908 |
| Ending Page | 914 |
| File Size | 461364 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424437702 |
| DOI | 10.1109/ITNG.2009.28 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-04-27 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | shill verification Uncertainty Data analysis Data security Quality of service Dempster-Shafer theory Data mining Information technology Computer science Information science online auctions auction fraud Shill bidding Pattern matching Testing |
| Content Type | Text |
| Resource Type | Article |
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