Preserving privacy and assuring integrity in data aggregation for wireless sensor networks

  • Rabindra Bista*
  • , Myoung Seon Song
  • , Jae Woo Chang
  • *Corresponding author for this work

    Research output: Contribution to conferenceConference paperpeer-review

    Abstract

    Many applications require reliable and trustful data aggregation in Wireless Sensor Networks (WSNs). In this paper, we propose a new scheme to achieve data privacy and integrity protection in data aggregation for WSNs, called Preserving Privacy and Assuring Integrity (PPAI) scheme. For this, before data transmission, the PPAI scheme blurs the original sampled data of a sensor node by randomly breaking down the data two times independently into two unequal pieces for each time and combining each of the data pieces with a separate private seed of the sensor node. Through analytical performance evaluations, we show that the PPAI scheme is much more efficient in terms of both communication overhead and data propagation delay than the existing work to achieve data privacy and integrity assurance in data aggregation for WSNs.

    Original languageEnglish
    Title of host publication2010 IEEE International Conference on Networked Embedded Systems for Enterprise Applications, NESEA 2010
    DOIs
    StatePublished - 2010
    Event1st IEEE International Conference on Networked Embedded Systems for Enterprise Applications, NESEA 2010 - Suzhou, China
    Duration: 2010.11.252010.11.26

    Publication series

    Name2010 IEEE International Conference on Networked Embedded Systems for Enterprise Applications, NESEA 2010

    Conference

    Conference1st IEEE International Conference on Networked Embedded Systems for Enterprise Applications, NESEA 2010
    Country/TerritoryChina
    CitySuzhou
    Period10.11.2510.11.26

    Keywords

    • Component
    • Data aggregation
    • Data integrity
    • Data privacy
    • Wireless sensor network

    Quacquarelli Symonds(QS) Subject Topics

    • Computer Science & Information Systems
    • Data Science

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