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The cookie recipe: Untangling the use of cookies in the wild
Umeå University, Faculty of Science and Technology, Department of Computing Science.
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2017 (English)In: TMA Conference 2017: Proceedings of the 1st Network Traffic Measurement and Analysis Conference, IEEE, 2017, no C 2014. Proceedings: LNCS 8783InformationSecurity 17th International Confe= nce, ISC 2014, 12-14 Oct. 2014, Hong Kong, China, P309 osh A., 2015, ACM Transactions on Economics and Computation, V3,=20 vakorn Suphannee, 2016, 2016 IEEE SYMPOSIUM ON SECURITY AND PRIVACY (SP)I=Conference paper, Published paper (Refereed)
Abstract [en]

Users online are commonly tracked using HTTP cookies when browsing on the web. To protect their privacy, users tend to use simple tools to block the activity of HTTP cookies. However, the "block all" design of tools breaks critical web services or severely limits the online advertising ecosystem. Therefore, to ease this tension, a more nuanced strategy that discerns better the intended functionality of the HTTP cookies users encounter is required. We present the first large-scale study of the use of HTTP cookies in the wild using network traces containing more than 5.6 billion HTTP requests from real users for a period of two and a half months. We first present a statistical analysis of how cookies are used. We then analyze the structure of cookies and observe that; HTTP cookies are significantly more sophisticated than the name=3Dvalue defined by the standard and assumed by researchers and developers. Based on our findings we present an algorithm that is able to extract the information included in 86% of the cookies in our dataset with an accuracy of 91.7%. Finally, we discuss the implications of our findings and provide solutions that can be used to improve the most promising privacy preserving tools.

Place, publisher, year, edition, pages
IEEE, 2017. no C 2014. Proceedings: LNCS 8783InformationSecurity 17th International Confe= nce, ISC 2014, 12-14 Oct. 2014, Hong Kong, China, P309 osh A., 2015, ACM Transactions on Economics and Computation, V3,=20 vakorn Suphannee, 2016, 2016 IEEE SYMPOSIUM ON SECURITY AND PRIVACY (SP)I=
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Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-146182DOI: 10.23919/TMA.2017.8002896ISI: 000426454700001ISBN: 978-3-901882-95-1 (electronic)OAI: oai:DiVA.org:umu-146182DiVA, id: diva2:1194472
Conference
2017 Network Traffic Measurement and Analysis Conference (TMA), Dublin, Ireland, June 21-23, 2017
Available from: 2018-04-03 Created: 2018-04-03 Last updated: 2018-06-09Bibliographically approved

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Jiang, Lili

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Citation style
  • apa
  • ieee
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