• DocumentCode
    3301671
  • Title

    Privacy preserving high utility mining based on genetic algorithms

  • Author

    Chun-Wei Lin ; Tzung-Pei Hong ; Jia-Wei Wong ; Guo-Cheng Lan

  • Author_Institution
    Innovative Inf. Ind. Res. Center, Harbin Inst. of Technol., Shenzhen, China
  • fYear
    2013
  • fDate
    13-15 Dec. 2013
  • Firstpage
    191
  • Lastpage
    195
  • Abstract
    In this paper, a GA-based privacy-preserving utility mining method is proposed to delete appropriate transactions for hiding sensitive high utility itemsets from a database. The downward closure property and the pre-large concepts are adopted in the proposed algorithm to reduce the cost of rescanning databases. Experiments are also conducted to evaluate the performance of the proposed approach in execution time and the amount of side-effects.
  • Keywords
    data mining; data privacy; database management systems; genetic algorithms; GA-based privacy-preserving utility mining method; downward closure property; execution time; genetic algorithms; pre-large concepts; Biological cells; Data mining; Genetic algorithms; Itemsets; Sociology; Statistics; evolutionary computation; genetic algorithm; pre-large concept; privacy preserving; utility mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2013 IEEE International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/GrC.2013.6740406
  • Filename
    6740406