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dc.identifier.urihttp://hdl.handle.net/11401/77240
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeThesis
dcterms.abstractTraffic 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.
dcterms.available2017-09-20T16:52:15Z
dcterms.contributorPolychronakis, Michalisen_US
dcterms.contributorGill, Phillipaen_US
dcterms.contributorDas, Samir.en_US
dcterms.creatorLi, Anke
dcterms.dateAccepted2017-09-20T16:52:15Z
dcterms.dateSubmitted2017-09-20T16:52:15Z
dcterms.descriptionDepartment of Computer Scienceen_US
dcterms.extent52 pg.en_US
dcterms.formatApplication/PDFen_US
dcterms.formatMonograph
dcterms.identifierhttp://hdl.handle.net/11401/77240
dcterms.issued2016-12-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2017-09-20T16:52:15Z (GMT). No. of bitstreams: 1 Li_grad.sunysb_0771M_13125.pdf: 2663267 bytes, checksum: ea9462235ecd4412b66156aa452e0d7b (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectInternet Censorship, Mobile networks, Network measurement, Network neutrality, Traffic differentiation
dcterms.subjectComputer science
dcterms.titleMeasuring Internet Traffic Manipulation
dcterms.typeThesis


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