會議論文

學年 98
學期 1
發表日期 2009-12-03
作品名稱 An Early Fraud Detection Mechanism for Online Auctions Based on Phased Modeling
作品名稱(其他語言)
著者 Chang, Jau-Shien; Chang, Wen-Hsi
作品所屬單位 淡江大學資訊管理學系
出版者 Taipei : Institute of electrical and electronics engineers (IEEE)
會議名稱 2009 Joint Conferences on Pervasive Computing
會議地點 Taipei, Taiwan
摘要 Reputation systems provided by online auction sites are the only countermeasure available for buyers to evaluate a seller's credit. Unfortunately, feedback score mechanisms are too easily manipulated creating falsely overrated reputations. Therefore, developing an effective fraud detection method can assist the user in identifying cases of fraud. However, none of existing research addresses the most important issue of early fraud detection, which is, discovering a fraudster before he defrauds. For effective early fraud detection for online auctions, this paper proposes a novel phased detection framework to identify a potential fraudster as early as possible. To heighten precision in detection, different quantifiable behavioral features were extracted and integrated with regression model trees to build phased fraud behavior models. To demonstrate the effectiveness of the proposed method, real transaction data were collected from Taiwan's Yahoo!Kimo for training and testing. The experimental results with these models show that the recall rate of fraud detection is over 82%.
關鍵字
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 20091203~20091205
通訊作者
國別 TWN
公開徵稿 Y
出版型式
出處 Proceedings of the 2009 joint conferences on pervasive computing, pp.743-748
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