Fraud Detection in Electronic Auction

Auction frauds plague electronic auction websites. Unfortunately, no literature has tried to formulate and solve the problem. This paper aims to tackle it by suggesting a novel method to detect auction fraudsters, which involves determining and extracting characteristic features from exposed fraudsters, through analyzing the fraudsters’ transaction history which exists as a graph. We then use the features for detecting other potential fraudsters. Choosing the best features is a challenging and non-trivial task; however, with the features that we have currently selected, our method has already achieved a precision of 82% and a recall of 83% during an evaluation on some real test data from eBay. To demonstrate how our method can be used in real-world, we have developed a working Java prototype system which allows users to query the legitimacy of eBay users using our method.