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A Real-Time Monitoring Framework for Online Auctions Frauds

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Current Approaches in Applied Artificial Intelligence (IEA/AIE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9101))

Abstract

In spite of many advantages of online auctioning, serious frauds menace the auction users’ interests. Today, monitoring auctions for frauds is becoming very crucial. We propose here a generic framework that covers real-time monitoring of multiple live auctions. The monitoring is performed at different auction times depending on fraud types and auction duration. We divide the real-time monitoring functionality into threefold: detecting frauds, reacting to frauds, and updating bidders’ clusters. The first task examines in run-time bidding activities in ongoing auctions by applying fraud detection mechanisms. The second one determines how to react to suspicious activities by taking appropriate run-time actions against the fraudsters and infected auctions. Finally, every time an auction ends, successfully or unsuccessfully, participants’ fraud scores and their clusters are updated dynamically. Through simulated auction data, we conduct an experiment to monitor live auctions for shill bidding. The latter is considered the most severe fraud in online auctions, and the most difficult to detect. More precisely, we monitor each live auction at three time points, and for each of them, we verify the shill patterns that most likely happen.

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Authors and Affiliations

  1. Computer Science department, University of Regina, Regina, SK, Canada

    Samira Sadaoui, Xuegang Wang & Dongzhi Qi

Authors
  1. Samira Sadaoui
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  2. Xuegang Wang
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  3. Dongzhi Qi
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Corresponding author

Correspondence to Samira Sadaoui .

Editor information

Editors and Affiliations

  1. Texas State University, San Marcos, Texas, USA

    Moonis Ali

  2. Dongguk University, Seoul, Korea, Republic of (South Korea)

    Young Sig Kwon

  3. Dongguk University, Seoul, Korea, Republic of (South Korea)

    Chang-Hwan Lee

  4. Dongguk University, Seoul, Korea, Republic of (South Korea)

    Juntae Kim

  5. Seoul National University, Seoul, Korea, Republic of (South Korea)

    Yongdai Kim

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Sadaoui, S., Wang, X., Qi, D. (2015). A Real-Time Monitoring Framework for Online Auctions Frauds. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-19066-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19065-5

  • Online ISBN: 978-3-319-19066-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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