Crowd fraud detection in internet advertising

Tian Tian, Jun Zhu, Fen Xia, Xin Zhuang, Tong Zhang

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


The rise of crowdsourcing brings new types of malpractices in Internet advertising. One can easily hire web workers through malicious crowdsourcing platforms to attack other advertisers. Such human generated crowd frauds are hard to detect by conventional fraud detection methods. In this paper, we carefully examine the characteristics of the group behaviors of crowd fraud and identify three persistent patterns, which are moderateness, synchronicity and dispersivity. Then we propose an effective crowd fraud detection method for search engine advertising based on these patterns, which consists of a constructing stage, a clustering stage and a filtering stage. At the constructing stage, we remove irrelevant data and reorganize the click logs into a surferadvertiser inverted list; At the clustering stage, we define the sync-similarity between surfers' click histories and transform the coalition detection to a clustering problem, solved by a nonparametric algorithm; and finally we build a dispersity filter to remove false alarm clusters. The nonparametric nature of our method ensures that we can find an unbounded number of coalitions with nearly no human interaction. We also provide a parallel solution to make the method scalable to Web data and conduct extensive experiments. The empirical results demonstrate that our method is accurate and scalable.

Original languageEnglish (US)
Title of host publicationWWW 2015 - Proceedings of the 24th International Conference on World Wide Web
PublisherAssociation for Computing Machinery
Number of pages11
ISBN (Electronic)9781450334693
StatePublished - May 18 2015
Externally publishedYes
Event24th International Conference on World Wide Web, WWW 2015 - Florence, Italy
Duration: May 18 2015May 22 2015

Publication series

NameWWW 2015 - Proceedings of the 24th International Conference on World Wide Web


Other24th International Conference on World Wide Web, WWW 2015


  • Crowdsourcing
  • Fraud Detection
  • Internet Advertising

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software


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