• DocumentCode
    2496209
  • Title

    On syntactic anonymity and differential privacy

  • Author

    Clifton, C. ; Tassa, Tamir

  • Author_Institution
    Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA
  • fYear
    2013
  • fDate
    8-12 April 2013
  • Firstpage
    88
  • Lastpage
    93
  • Abstract
    Recently, there has been a growing debate over approaches for handling and analyzing private data. Research has identified issues with syntactic anonymity models. Differential privacy has been promoted as the answer to privacy-preserving data mining. We discuss here issues involved and criticisms of both approaches, and conclude that both have their place. We identify research directions that will enable greater access to data while improving privacy guarantees.
  • Keywords
    data mining; data privacy; differential privacy; privacy preserving data mining; private data analysis; syntactic anonymity models; Data models; Data privacy; Noise; Privacy; Publishing; Syntactics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering Workshops (ICDEW), 2013 IEEE 29th International Conference on
  • Conference_Location
    Brisbane, QLD
  • Print_ISBN
    978-1-4673-5303-8
  • Electronic_ISBN
    978-1-4673-5302-1
  • Type

    conf

  • DOI
    10.1109/ICDEW.2013.6547433
  • Filename
    6547433