Fake view analytics in online video services

Liang Chen, Yipeng Zhou, Dah Ming Chiu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

6 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 the 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 paper. We develop some algorithms and show their effectiveness for this problem.
Original languageEnglish
Title of host publicationNOSSDAV '14
Subtitle of host publicationProceedings of Network and Operating System Support on Digital Audio and Video Workshop
PublisherAssociation for Computing Machinery (ACM)
Pages1-6
Number of pages6
ISBN (Electronic)9781450327060
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event24th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2014 - Singapore, Singapore
Duration: 19 Mar 201420 Mar 2014

Conference

Conference24th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2014
CountrySingapore
CitySingapore
Period19/03/1420/03/14

Keywords

  • measurement
  • experimentation
  • reliability

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