Abstract

Internet auction fraud has become prevalent. Methodologies for detecting fraudulent transactions use historical information about Internet auction participants to decide whether or not a user is a potential fraudster. The information includes reputation scores, values of items, time frames of various activities and transaction records. This paper presents a distinctive set of fraudster characteristics based on an analysis of 278 allegations about the sale of counterfeit goods at Internet auction sites. Also, it applies a Bayesian approach to analyze the relevance of evidence in Internet auction fraud cases.

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