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ConXsense: automated context classification for context-aware access control

Published: 04 June 2014 Publication History
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  • Abstract

    We present ConXsense, the first framework for context-aware access control on mobile devices based on context classification. Previous context-aware access control systems often require users to laboriously specify detailed policies or they rely on pre-defined policies not adequately reflecting the true preferences of users. We present the design and implementation of a context-aware framework that uses a probabilistic approach to overcome these deficiencies. The framework utilizes context sensing and machine learning to automatically classify contexts according to their security and privacy-related properties. We apply the framework to two important smartphone-related use cases: protection against device misuse using a dynamic device lock and protection against sensory malware. We ground our analysis on a sociological survey examining the perceptions and concerns of users related to contextual smartphone security and analyze the effectiveness of our approach with real-world context data. We also demonstrate the integration of our framework with the FlaskDroid architecture for fine-grained access control enforcement on the Android platform.

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    cover image ACM Conferences
    ASIA CCS '14: Proceedings of the 9th ACM symposium on Information, computer and communications security
    June 2014
    556 pages
    ISBN:9781450328005
    DOI:10.1145/2590296
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 04 June 2014

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    Author Tags

    1. context sensing
    2. context-awareness
    3. mobile security
    4. privacy policies

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    ASIA CCS '14 Paper Acceptance Rate 50 of 255 submissions, 20%;
    Overall Acceptance Rate 418 of 2,322 submissions, 18%

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    • (2024)SHRIMPS: A framework for evaluating multi-user, multi-modal implicit authentication systemsComputers & Security10.1016/j.cose.2023.103594137(103594)Online publication date: Feb-2024
    • (2024)Advances in Privacy Preservation TechnologiesPrivacy Computing10.1007/978-981-99-4943-4_2(17-42)Online publication date: 13-Feb-2024
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