• DocumentCode
    3455069
  • Title

    Research on Diversity of Sensitive Attribute of K-Anonymity

  • Author

    Ren, Xiangmin ; Yang, Jing ; Wei, Fengmei

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
  • fYear
    2010
  • fDate
    27-28 Nov. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The common way to protect privacy is to use K-anonymity in data publishing. This paper will analyse comprehensively the current research situation of K-anonymity model used to prevent privacy leaked in data publishing, we study the characteristics of sensitive attribute diversity of K-Anonymity, and propose CBK(L,K)-Anonymity algorithm in order to solve the problem of privacy information leakage in publishing the data, it can make anonymous data effectively resist background knowledge attack and homogeneity attack , and can solve diversity of sensitive attribute. In addition, we will extend our ideas for handling how to solve privacy information leakage problem by using CBK(L,K)-Anonymity algorithm in another paper.
  • Keywords
    data privacy; publishing; CBK-anonymity algorithm; data publishing; k-anonymity attribute; privacy information leakage problem; privacy protection; sensitive attribute diversity; Algorithm design and analysis; Cancer; Clustering algorithms; Data privacy; Lungs; Privacy; Publishing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database Technology and Applications (DBTA), 2010 2nd International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6975-8
  • Electronic_ISBN
    978-1-4244-6977-2
  • Type

    conf

  • DOI
    10.1109/DBTA.2010.5659106
  • Filename
    5659106