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Measuring Internet Traffic Manipulation

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dc.contributor.advisor Gill, Phillipa en_US
dc.contributor.author Li, Anke en_US
dc.contributor.other Department of Computer Science en_US
dc.date.accessioned 2017-09-20T16:52:15Z
dc.date.available 2017-09-20T16:52:15Z
dc.date.issued 2016-12-01 en_US
dc.identifier.uri http://hdl.handle.net/11401/77240 en_US
dc.description 52 pgs en_US
dc.description.abstract Traffic differentiation---giving better or worse performance to certain classes of Internet traffic---is a well-known but poorly understood traffic management policy. There is active discussion on whether and how ISPs should be allowed to differentiate Internet traffic, but little data about current practices to inform this discussion. Previous work attempted to address this problem for fixed line networks, but at the time of the publication of our work, there was no solution that works in the more challenging mobile environment. In terms of censorship measurement, despite the high perceived value and increasing severity of online information controls, a data-driven understanding of the phenomenon has remained elusive. In this report, we first present the design, implementation and evaluation of Differentiation Detector, the first system and mobile app for identifying traffic differentiation for arbitrary applications in the mobile environment. Next we introduce Information Controls Lab (ICLab)---a project focused on collecting and analyzing reliable information controls data on the Internet at scale---by comparing it with another design point in the space of Internet censorship measurement with particular emphasis on how they address the challenges of locating vantage points, choosing content to test, and analyzing results. We discuss the trade offs of decisions made by each platform and show how the resulting data provides complementary views of global censorship, as well as the lessons learned and open challenges discovered through our experiences. en_US
dc.description.sponsorship This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. en_US
dc.format Monograph en_US
dc.format.medium Electronic Resource en_US
dc.language.iso en_US en_US
dc.publisher The Graduate School, Stony Brook University: Stony Brook, NY. en_US
dc.subject.lcsh Computer science en_US
dc.subject.other Internet Censorship, Mobile networks, Network measurement, Network neutrality, Traffic differentiation en_US
dc.title Measuring Internet Traffic Manipulation en_US
dc.type Thesis en_US
dc.mimetype Application/PDF en_US
dc.contributor.committeemember Polychronakis, Michalis en_US
dc.contributor.committeemember Das, Samir en_US


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