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dc.contributor.authorLivshits, Benjamin
dc.contributor.authorDavidson, Drew
dc.date.accessioned2012-03-27T15:18:03Z
dc.date.available2012-03-27T15:18:03Z
dc.date.issued2012-03-26
dc.identifier.citationTR1714
dc.identifier.urihttp://digital.library.wisc.edu/1793/60867
dc.description.abstractWe present MoRePriv, a system that combines the goals of privacy and content personalization in the browser. MoRePriv discovers user interests and shares them with third-parties, but only with the explicit per- mission of the user. We demonstrate how always-on user interest mining can effectively infer user interests in a mobile operating system. Inference is based on parsing and classifying multiple stream of (sensitive) informa- tion about the user, such as their email, SMS, Facebook stream, and network communications. This paper positions MoRePriv as an OS-level ser- vice that exposes information about the user in the form of a persona to applications. This provides easy-to-use APIs and limits the potential for information leaks. Us- ing a number of cases studies, we demonstrate how var- ious personalization tasks can be achieved with the help of MoRePriv.en
dc.subjectPersonalization, Privacy, Mobile Computingen
dc.titleMoRePriv: Mobile OS-Wide Application Personalizationen
dc.typeTechnical Reporten


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    Technical Reports Archive for the Department of Computer Sciences at the University of Wisconsin-Madison

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