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    ACM HotMobile 2013 Poster: An Energy Efficient Semantic Context Model for Managing Privacy on Smartphones

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    Links to Files
    https://ebiquity.umbc.edu/paper/html/id/617/ACM-HotMobile-2013-Poster-An-Energy-Efficient-Semantic-Context-Model-for-Managing-Privacy-on-Smartphones
    Permanent Link
    http://hdl.handle.net/11603/11850
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    • UMBC Computer Science and Electrical Engineering Department
    • UMBC Faculty Collection
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    Metadata
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    Author/Creator
    Das, Prajit Kumar
    Ghosh, Dibyajyoti
    Joshi, Anupam
    Finin, Tim
    Date
    2013-07-01
    Type of Work
    2 pages
    Text
    posters
    Citation of Original Publication
    Prajit Kumar Das, Dibyajyoti Ghosh, Anupam Joshi, and Tim Finin, ACM HotMobile 2013 Poster: An Energy Efficient Semantic Context Model for Managing Privacy on Smartphones, SIGMOBILE Mob. Comput. Commun. Rev., 2013, https://ebiquity.umbc.edu/paper/html/id/617/ACM-HotMobile-2013-Poster-An-Energy-Efficient-Semantic-Context-Model-for-Managing-Privacy-on-Smartphones
    Rights
    This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
    Subjects
    android
    context-aware
    energy efficient
    mobile
    UMBC Ebiquity Research Group
    Abstract
    Modern smartphones are capable of gathering massive amounts of data about a user and her context. While this data is mostly utilized for providing services that are better suited to the user, user data and context leakage from smart phones can have disastrous results. This is especially true as most enterprises are going to a Bring-Your-Own-Device (BYOD) model for mobile devices such as smartphones. We recognize this change as a potential threat to data privacy, both of the user and also of corporations whose data is on employee owned phones. We describe a method to carry out energy efficient privacy preservation on a mobile smart-phone. Our work is based on a study of an Android smartphone’s component-wise energy consumption pattern and is based on a three-fold approach to ensure efficient execution of privacy policies, based on user and app context modeled using semantic web technologies.


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    Albin O. Kuhn Library & Gallery
    University of Maryland, Baltimore County
    1000 Hilltop Circle
    Baltimore, MD 21250
    www.umbc.edu/scholarworks

    Contact information:
    Email: scholarworks-group@umbc.edu
    Phone: 410-455-3021


    If you wish to submit a copyright complaint or withdrawal request, please email mdsoar-help@umd.edu.