• DocumentCode
    2213644
  • Title

    Privacy preserving based on association rule mining

  • Author

    Ma, Tinghuai ; Wang, Sainan ; Liu, Zhong

  • Author_Institution
    Sch. of Comput. & Software, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    20-22 Aug. 2010
  • Abstract
    Privacy has become an important issue in Data Mining. Many methods have been brought out to solve this problem. This paper deals with the problem of association rule mining which preserves the confidentiality of each database. In order to find the association rule, each participant has to share their own data. Thus, much privacy information may be broadcast or been illegal used. These issues can be divided into two categories: data hiding and knowledge hiding. This paper reviews the major method of privacy preserving on each category and choose some of them to complete our system. At the end, an improvement of sensitive rules hiding is proposed to make it more accuracy and security.
  • Keywords
    data mining; data privacy; association rule mining; data hiding category; data mining; knowledge hiding category; privacy preserving method; sensitive rules hiding; Book reviews; Cryptography; Itemsets; Variable speed drives; Association-rule; data hinding; data mining; knowledge hiding; privacy preserving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2154-7491
  • Print_ISBN
    978-1-4244-6539-2
  • Type

    conf

  • DOI
    10.1109/ICACTE.2010.5578938
  • Filename
    5578938