A proposed data mining approach for internet auction fraud detection

Authors:
Yungchang Ku;Yuchi Chen;Chaochang Chiu
Affiliations:
Department of Information Management, Yuan Ze University, Chung-Li, Taoyuan, Taiwan;Department of Information Management, Yuan Ze University, Chung-Li, Taoyuan, Taiwan;Department of Information Management, Yuan Ze University, Chung-Li, Taoyuan, Taiwan
Venue:
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Year:
2007

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Abstract

Internet auctions are one of the few successful new business models. Owing to the nature of Internet auctions, e.g. high degree of anonymity, relaxed legal constraints, and low costs for entry and exit, etc..., fraudsters are easily to setup a scam or deception in auction activities. Undeniable fact is that information asymmetry between sellers and buyers and lacking of immediately examining authenticity of the merchandise, the buyer can't verify the seller and the characteristics of the merchandise until after the transaction is completed. This paper proposes a simple method which is detected potential fraudster by social network analysis (SNA) and decision tree to provide a feasible mechanism of playing capable guardians in buyers' auction activities. Through our simple method, buyers can easily avoid defraud in auction activities.