Detectives: Detecting coalition hit inflation attacks in advertising networks streams

Ahmed Metwally, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

73 Citations (Scopus)

Abstract

Click fraud is jeopardizing the industry of Internet advertising. Internet advertising is crucial for the thriving of the entire Internet, since it allows producers to advertise their products, and hence contributes to the well being of e-commerce. Moreover, advertising supports the intellectual value of the Internet by covering the running expenses of publishing content. Some content publishers are dishonest, and use automation to generate traffic to defraud the advertisers. Similarly, some advertisers automate clicks on the advertisements of their competitors to deplete their competitors' advertising budgets. This paper describes the advertising network model, and focuses on the most sophisticated type of fraud, which involves coalitions among fraudsters. We build on several published theoretical results to devise the Similarity-Seeker algorithm that discovers coalitions made by pairs of fraudsters. We then generalize the solution to coalitions of arbitrary sizes. Before deploying our system on a real network, we conducted comprehensive experiments on data samples for proof of concept. The results were very accurate. We detected several coalitions, formed using various techniques, and spanning numerous sites. This reveals the generality of our model and approach.

Original languageEnglish
Title of host publication16th International World Wide Web Conference, WWW2007
Pages241-250
Number of pages10
DOIs
Publication statusPublished - 22 Oct 2007
Event16th International World Wide Web Conference, WWW2007 - Banff, AB, Canada
Duration: 8 May 200712 May 2007

Publication series

Name16th International World Wide Web Conference, WWW2007

Other

Other16th International World Wide Web Conference, WWW2007
CountryCanada
CityBanff, AB
Period8/5/0712/5/07

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Keywords

  • Approximate set similarity
  • Click spam detection
  • Cliques enumeration
  • Coalition fraud attacks
  • Real data experiments
  • Similarity-sensitive sampling

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Metwally, A., Agrawal, D., & El Abbadi, A. (2007). Detectives: Detecting coalition hit inflation attacks in advertising networks streams. In 16th International World Wide Web Conference, WWW2007 (pp. 241-250). (16th International World Wide Web Conference, WWW2007). https://doi.org/10.1145/1242572.1242606