Detecting Coalition Attacks in Online Advertising: A hybrid data mining approach

  • Received: 01 February 2016 Revised: 01 September 2016 Published: 01 July 2016
  • Coalition attack is nowadays one of the most common type of attacks in the industry of online advertising. In this paper, we attempt to mitigate the problem of frauds by proposing a hybrid framework that detects the coalition attacks based on multiple metrics. We also articulate the theoretical basis for these metrics to be integrated into the hybrid framework. Furthermore, we instance the framework with two metrics and develop a detection system that identifies the coalition attacks from two distinguish perspectives.

    Citation: Qinglei Zhang, Wenying Feng. Detecting Coalition Attacks in Online Advertising: A hybrid data mining approach[J]. Big Data and Information Analytics, 2016, 1(2): 227-245. doi: 10.3934/bdia.2016006

    Related Papers:

  • Coalition attack is nowadays one of the most common type of attacks in the industry of online advertising. In this paper, we attempt to mitigate the problem of frauds by proposing a hybrid framework that detects the coalition attacks based on multiple metrics. We also articulate the theoretical basis for these metrics to be integrated into the hybrid framework. Furthermore, we instance the framework with two metrics and develop a detection system that identifies the coalition attacks from two distinguish perspectives.


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