Analysis and detection of fake views in online video services

Liang Chen, Yipeng Zhou, Dah Ming Chiu

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Online video-on-demand (VoD) services invariably maintain a view count for each video they serve, and it has become an important currency for various stakeholders, from viewers, to content owners, advertizers, and the online service providers themselves. There is often significant financial incentive to use a robot (or a botnet) to artificially create fake views. How can we detect fake views? Can we detect them (and stop them) efficiently? What is the extent of fake views with current VoD service providers? These are the questions we study in this article. We develop some algorithms and show that they are quite effective for this problem.
Original languageEnglish
Article number44
Number of pages20
JournalACM Transactions on Multimedia Computing, Communications and Applications
Volume11
Issue number2s
DOIs
Publication statusPublished - Feb 2015
Externally publishedYes

Keywords

  • fake view
  • online video service
  • Fake view
  • Online video service

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