• DocumentCode
    2143437
  • Title

    Hiding Sensitive Association Rules on Stars

  • Author

    Wang, Shyue-Liang ; Hong, Tzung-Pei ; Tsai, Yu-Chuan ; Kao, Hung-Yu

  • Author_Institution
    Dept. of Inf. Manage., Eng. Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
  • fYear
    2010
  • fDate
    14-16 Aug. 2010
  • Firstpage
    505
  • Lastpage
    508
  • Abstract
    Current technology for association rules hiding mostly applies to data stored in a single transaction table. This work presents a novel algorithm for hiding sensitive association rules in data warehouses. A data warehouse is typically made up of multiple dimension tables and a fact table as in a star schema. Based on the strategies of reducing the confidence of sensitive association rule and without constructing the whole joined table, the proposed algorithm can effectively hide multi-relational association rules. Examples and analyses are given to demonstrate the efficacy of the approach.
  • Keywords
    data encapsulation; data mining; data warehouses; data warehouses; fact table; multi-relational association rules; multiple dimension tables; sensitive association rules hiding; single transaction table; star schema; Algorithm design and analysis; Association rules; Data privacy; Data warehouses; Itemsets; Association rule; Data mining; Hiding; Multi-relational; Privacy preserving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2010 IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4244-7964-1
  • Type

    conf

  • DOI
    10.1109/GrC.2010.123
  • Filename
    5575977