Scalability in privacy-preserving data aggregation for wireless sensor networks

  • Rabindra Bista*
  • , Young Sung Shin
  • , Jae Woo Chang
  • *Corresponding author for this work

    Research output: Contribution to conferenceConference paperpeer-review

    Abstract

    In this paper, we propose a new privacy preserving data aggregation scheme for WSNs. Our scheme applies additive property of complex numbers in order to combine sensor data and preserve data privacy during transmission to the sink node. In addition, for supporting scalability, we propose a novel mechanism in which a special set of real numbers are assigned to sensor nodes as their IDs so that a single bit is sufficient to hold ID of a sensor node during transmission of aggregated data to the sink node. For this, we, first, generate fixed size signatures for the IDs of all sensor nodes and then superimpose the signatures during data aggregation phase. By analytical evaluations, we show that our scheme is more scalable and energy efficient than the existing methods to achieve data privacy and transmit IDs of sensor nodes along with the aggregated data to the sink node.

    Original languageEnglish
    Title of host publicationProceedings - International Symposium on Parallel and Distributed Processing with Applications, ISPA 2010
    Pages192-199
    Number of pages8
    DOIs
    StatePublished - 2010
    EventInternational Symposium on Parallel and Distributed Processing with Applications, ISPA 2010 - Taipei, Taiwan, Province of China
    Duration: 2010.09.62010.09.9

    Publication series

    NameProceedings - International Symposium on Parallel and Distributed Processing with Applications, ISPA 2010

    Conference

    ConferenceInternational Symposium on Parallel and Distributed Processing with Applications, ISPA 2010
    Country/TerritoryTaiwan, Province of China
    CityTaipei
    Period10.09.610.09.9

    Keywords

    • Component
    • Data aggregation
    • Data privacy
    • Scalability
    • Signature
    • Wireless sensor network

    Quacquarelli Symonds(QS) Subject Topics

    • Computer Science & Information Systems
    • Data Science

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