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Demo: System-E: Enhancing privacy on mobile systems through content-based classification and storage

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Mobile systems face privacy challenges including coarse-grained privacy control and the inability to distinguish private and public files. We propose System-E, a novel system which can enhance the user privacy on mobile systems (e.g., Android) by (1) enabling users to set finer grained permissions for apps accessing data, and (2) enabling automatic classification of data (e.g., photos) at the storage layer (e.g., by using deep learning) to prevent potentially sensitive data from being stored/accessed with open permissions.

Original languageEnglish
Title of host publicationMobiSys 2018 - Proceedings of the 16th ACM International Conference on Mobile Systems, Applications, and Services
PublisherAssociation for Computing Machinery
Pages539
Number of pages1
ISBN (Electronic)9781450357203
DOIs
StatePublished - Jun 10 2018
Event16th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2018 - Munich, Germany
Duration: Jun 10 2018Jun 15 2018

Publication series

NameMobiSys 2018 - Proceedings of the 16th ACM International Conference on Mobile Systems, Applications, and Services

Conference

Conference16th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2018
Country/TerritoryGermany
CityMunich
Period06/10/1806/15/18

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