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    Integration of situational and reward elements for fair privacy principles and preferences (F3P)

    20133_downloaded_stream_121.pdf (477.0Kb)
    Access Status
    Open access
    Authors
    Skinner, Geoffrey
    Han, Song
    Chang, Elizabeth
    Date
    2006
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Skinner, G. and Han, Song and Chang, Elizabeth. 2006. : Integration of situational and reward elements for fair privacy principles and preferences (F3P), in Mohanty, S.P. and Sahoo, A. (ed), International Conference on Industrial Technology, Dec 15 2006, pp. 3078-3083. Mumbai, India: IEEE Computer Society Press.
    Source Title
    International Conference on Industrial Technology (ICIT 2006)
    Source Conference
    International Conference on Industrial Technology
    Faculty
    Curtin Business School
    School
    Centre for Extended Enterprises and Business Intelligence
    Remarks

    Copyright 2006 IEEE

    This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/34383
    Collection
    • Curtin Research Publications
    Abstract

    It is widely acknowledged that Information Privacy is subjective in nature and contextually influenced. Individuals value their personal privacy differently with many willing to trade-off of privacy for some form of reward or personal gain. Many of the proposed privacy protection schemes do not give due consideration to the contextual, and more importantly situational influence on privacy. Rather privacy preferences for personal data are configurable for only a limited set of notions that include purpose, recipient, category, and condition. Current solutions offer no, or very limited, support for individual situational privacy preferences. This paper proposes a conceptual framework that allows entities to assign privacy preferences to their personal data items that incorporate situation and reward elements. The solution allows entities to assign trade-off values to their personal data based on the situation and context of the data request. In this manner the data owners set what they perceive as fair privacy practices and preferences for evaluating the worth of their personal data.

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