English  |  正體中文  |  简体中文  |  Items with full text/Total items : 56859/90577 (63%)
Visitors : 12294242      Online Users : 53
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/97923

    Title: Analysis of fraudulent behavior strategies in online auctions for detecting latent fraudsters
    Authors: Chang, Jau-Shien;Chang, Wen-Hsi
    Contributors: 淡江大學資訊管理學系
    Keywords: Early fraud detection;Behavior fluctuation;Clustering;Online auction;E-commerce
    Date: 2014-03-01
    Issue Date: 2014-04-28 15:13:06 (UTC+8)
    Publisher: Amsterdam: Elsevier BV
    Abstract: Online auction fraudsters constantly monitor the contextual situations of the auction and change their behavior strategies accordingly to distract the attention of their targets. This flipping of behavior makes it difficult to identify fraudsters. Thus, legitimate traders need appropriate countermeasures to avoid becoming victimized. To help online auction users detect fraudsters as early as possible, this study develops a systematic method to discover the fraudulent strategies from proven cases of online auction fraud. First, according to the results of cluster analysis on the proven fraudsters, four typical types of fraud are identified, which are Aggressive, Classical, Luxury and Low-profiled. To provide better insight, a strategy is further represented by a series of status transitions. Hidden statuses of latent fraudsters are discovered by applying X-means clustering to the phased profiles of their transaction histories. As a result, various strategies can be extracted by such a systematic method and interesting characteristics are found in these strategies. For example, about 80% fraudsters in the Yahoo!Taiwan auction site flip their behavior no more than two times, which is not as complicated as expected originally. Based on these discovered fraudulent statuses, a high-resolution fraud detection method is performed to classify suspects into legitimate users or fraudsters in different statuses, potentially improving overall detection accuracy. A two-way monitoring procedure is then proposed to successively examine the statuses of a suspicious account. Analysis shows that the two-way monitoring method is promising for better detection of well-camouflaged fraudsters.
    Relation: Electronic Commerce Research and Applications 13(2), pp.79–97
    DOI: 10.1016/j.elerap.2013.10.004
    Appears in Collections:[Graduate Institute & Department of Information Management] Journal Article

    Files in This Item:

    File Description SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback