• DocumentCode
    247081
  • Title

    New Data Publishing Framework in the Big Data Environments

  • Author

    Jun Yang ; Zheli Liu ; Chunfu Jia ; Kai Lin ; Zijing Cheng

  • Author_Institution
    Coll. of Comput. & Control Eng., Nankai Univ., Tianjin, China
  • fYear
    2014
  • fDate
    8-10 Nov. 2014
  • Firstpage
    363
  • Lastpage
    366
  • Abstract
    The traditional data publishing methods will remove the sensitive attributes and generate the abundant records to achieve the goal of privacy protection. In the big data environment, they cannot satisfy some data mining tasks with privacy considerations. This paper provides a new data publishing framework. It can preserve the data integrity, i.e., the original data structure is preserved, and it doesn´t require deleting any attribute and adding k-times data to achieve anonymity.
  • Keywords
    Big Data; cryptography; data integrity; data mining; data privacy; data structures; anonymity; big data environment; data integrity preservation; data mining; data publishing framework; data publishing method; data structure preservation; decyption; encyption; privacy considerations; privacy protection; Data mining; Databases; Encryption; Privacy; Publishing; data publishing; big data; format-preserving encryption; data mask;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2014 Ninth International Conference on
  • Conference_Location
    Guangdong
  • Type

    conf

  • DOI
    10.1109/3PGCIC.2014.139
  • Filename
    7024610