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Netprobe: a fast and scalable system for fraud detection in online auction networks

9 years 11 months ago
Netprobe: a fast and scalable system for fraud detection in online auction networks
Given a large online network of online auction users and their histories of transactions, how can we spot anomalies and auction fraud? This paper describes the design and implementation of NetProbe, a system that we propose for solving this problem. NetProbe models auction users and transactions as a Markov Random Field tuned to detect the suspicious patterns that fraudsters create, and employs a Belief Propagation mechanism to detect likely fraudsters. Our experiments show that NetProbe is both efficient and effective for fraud detection. We report experiments on synthetic graphs with as many as 7,000 nodes and 30,000 edges, where NetProbe was able to spot fraudulent nodes with over 90% precision and recall, within a matter of seconds. We also report experiments on a real dataset crawled from eBay, with nearly 700,000 transactions between more than 66,000 users, where NetProbe was highly effective at unearthing hidden networks of fraudsters, within a realistic response time of about ...
Shashank Pandit, Duen Horng Chau, Samuel Wang, Chr
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2007
Where WWW
Authors Shashank Pandit, Duen Horng Chau, Samuel Wang, Christos Faloutsos
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