Online tracking: A 1-million-site measurement and analysis

Steven Englehardt, Arvind Narayanan

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

169 Scopus citations

Abstract

We present the largest and most detailed measurement of online tracking conducted to date, based on a crawl of the top 1 million websites. We make 15 types of measurements on each site, including stateful (cookie-based) and stateless (fingerprinting-based) tracking, the effect of browser privacy tools, and the exchange of tracking data between different sites ("cookie syncing"). Our findings include multiple sophisticated fingerprinting techniques never before measured in the wild. This measurement is made possible by our open-source web privacy measurement tool, OpenWPM1, which uses an automated version of a full-edged consumer browser. It supports parallelism for speed and scale, automatic recovery from failures of the underlying browser, and comprehensive browser instrumentation. We demonstrate our platform's strength in enabling researchers to rapidly detect, quantify, and characterize emerging online tracking behaviors.

Original languageEnglish (US)
Title of host publicationCCS 2016 - Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages1388-1401
Number of pages14
ISBN (Electronic)9781450341394
DOIs
StatePublished - Oct 24 2016
Event23rd ACM Conference on Computer and Communications Security, CCS 2016 - Vienna, Austria
Duration: Oct 24 2016Oct 28 2016

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
Volume24-28-October-2016
ISSN (Print)1543-7221

Other

Other23rd ACM Conference on Computer and Communications Security, CCS 2016
CountryAustria
CityVienna
Period10/24/1610/28/16

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications

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  • Cite this

    Englehardt, S., & Narayanan, A. (2016). Online tracking: A 1-million-site measurement and analysis. In CCS 2016 - Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (pp. 1388-1401). (Proceedings of the ACM Conference on Computer and Communications Security; Vol. 24-28-October-2016). Association for Computing Machinery. https://doi.org/10.1145/2976749.2978313