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Detecting Coalition Frauds in Online-Advertising

In: Mathematical and Computational Approaches in Advancing Modern Science and Engineering

Author

Listed:
  • Qinglei Zhang

    (Trent University)

  • Wenying Feng

    (Trent University)

Abstract

Online advertising becomes to play a major role in the global advertising industry. Meanwhile, since publishers have strong incentives to maximize the number of views, clicks, and conversions on advertisements, the publisher fraud is a severer problem for advertisers and worth the endeavor to detect and prevent them. By reviewing the literature of the frauds in online advertising, the frauds can be categorized as non-coalition attacks and coalition attacks in general. In this paper, we attempt to mitigate the problem of coalition frauds by proposing a new hybrid detecting approach that identifies the coalition frauds from both economic and traffic perspectives. Moreover, we propose an algorithm to detect the coalition frauds efficiently with an inductive style and greedy strategy.

Suggested Citation

  • Qinglei Zhang & Wenying Feng, 2016. "Detecting Coalition Frauds in Online-Advertising," Springer Books, in: Jacques Bélair & Ian A. Frigaard & Herb Kunze & Roman Makarov & Roderick Melnik & Raymond J. Spiteri (ed.), Mathematical and Computational Approaches in Advancing Modern Science and Engineering, pages 595-605, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-30379-6_54
    DOI: 10.1007/978-3-319-30379-6_54
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