• DocumentCode
    3768791
  • Title

    Efficient e-health data release with consistency guarantee under differential privacy

  • Author

    Hongwei Li;Yuanshun Dai; Xiaodong Lin

  • Author_Institution
    School of Computer Science and Engineering, University of Electronic Science and Technology of China, China
  • fYear
    2015
  • Firstpage
    602
  • Lastpage
    608
  • Abstract
    E-health data release, which answers the statistical queries of the Electronic Health Records (EHRs), has been widely adopted in modern health care services. However, since the EHRs contain sensitive information of the patients, the data release procedure may lead to the leakage of the privacy of patients if it is done without necessary protection measures in place. On addressing this, existing research literature introduces differential privacy to provide the necessary privacy guarantee. However, it is not suitable in sensitive e-health environments because it lacks the efficiency for data processing and updating. In this paper, we propose an efficient e-health data release scheme with consistency guarantee under differential privacy. Specifically, we improve the performance of the previous work by designing a new private partition algorithm of histogram and also proposing a heuristic hierarchical query method. We conduct real experiments and compare our scheme with the existing one to show that the proposal is more efficient in terms of data processing and updating. Moreover, we increase the accuracy of data release through consistency and give proof of privacy to show that the proposed algorithm is under ϵ-differential privacy.
  • Keywords
    "Privacy","Histograms","Partitioning algorithms","Data privacy","Databases","Vegetation","Inference algorithms"
  • Publisher
    ieee
  • Conference_Titel
    E-health Networking, Application & Services (HealthCom), 2015 17th International Conference on
  • Type

    conf

  • DOI
    10.1109/HealthCom.2015.7454576
  • Filename
    7454576