• DocumentCode
    580158
  • Title

    Privacy-preserving data mining demonstrator

  • Author

    Beck, Martin ; Marhöfer, Michael

  • Author_Institution
    Tech. Univ. Dresden, Dresden, Germany
  • fYear
    2012
  • fDate
    8-11 Oct. 2012
  • Firstpage
    210
  • Lastpage
    216
  • Abstract
    We present a system for demonstrating anonymized data mining on user profiles, which also evaluates the remaining utility of the generalized information through comparison of the classification results. The use case for this scenario builds around profiles containing personally identifiable information, which should be analyzed and classified by a third party. Our goal is to preserve the privacy of the users while maintaining a certain level of utility to allow data mining over the anonymized information.
  • Keywords
    data mining; data privacy; anonymized data mining; privacy-preserving data mining demonstrator; user privacy preservation; user profiles; Accuracy; Data models; Data privacy; Privacy; Runtime; Training; anonymization; data utility; demo; privacy preserving data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence in Next Generation Networks (ICIN), 2012 16th International Conference on
  • Conference_Location
    Berlin
  • Print_ISBN
    978-1-4673-1527-2
  • Electronic_ISBN
    978-1-4673-1525-8
  • Type

    conf

  • DOI
    10.1109/ICIN.2012.6376028
  • Filename
    6376028