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    User-Centric Dependence Analysis For Identifying Malicious Mobile Apps

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    ElishMaliciousMobile2012.pdf (166.3Kb)
    Downloads: 147
    Date
    2012
    Author
    Elish, Karim O.
    Yao, Danfeng (Daphne)
    Ryder, Barbara G.
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    Abstract
    This paper describes an efficient approach for identifying malicious Android mobile applications through specialized static program analysis. Our solution performs offline analysis and enforces the normal properties of legitimate dataflow patterns to identify programs that violate these properties. To demonstrate the feasibility of our user-centric dependence analysis, we implement a tool to generate a data dependence graph and perform preliminary evaluation to characterize both legitimate and malicious Android apps. Our preliminary results confirm our hypothesis on the differences in user-centric data dependence behaviors between legitimate and malicious apps.
    URI
    http://hdl.handle.net/10919/84191
    Collections
    • Destination Area: Integrated Security (IS) [119]
    • Scholarly Works, Department of Computer Science [408]

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