• DocumentCode
    541811
  • Title

    Privacy preserving data mining based on association rule- a survey

  • Author

    Vijayarani, S. ; Tamilarasi, A. ; SeethaLakshmi, R.

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Bharathiar Univ., Coimbatore, India
  • fYear
    2010
  • fDate
    27-29 Dec. 2010
  • Firstpage
    99
  • Lastpage
    103
  • Abstract
    Data mining is the process of extracting hidden information from the database. Data mining is emerging as one of the key features of many business organizations. The current trend in business collaboration shares the data and mined results to gain mutual benefit. The problem of privacy-preserving data mining has become more important in recent years because of the increasing ability to store personal data about users, and the increasing sophistication of data mining algorithms to leverage this information. Apart from classification and regression, one of the most important tasks of data mining is to find patterns in data. In particular, new advances in data mining and knowledge discovery that allow for the extraction of hidden knowledge in enormous amount of data impose new threats on the seamless integration of information. In this paper, we consider the problem of building privacy preserving algorithms for one category of data mining techniques, the association rule mining.
  • Keywords
    business data processing; data mining; data privacy; information retrieval; pattern classification; regression analysis; association rule mining; business collaboration; business organization; data pattern; data sharing; hidden information extraction; knowledge discovery; mutual benefit; privacy preserving data mining; Algorithm design and analysis; Association rules; Data privacy; Distributed databases; Itemsets; Association rule; Data Mining; Privacy Preserving Data Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication and Computational Intelligence (INCOCCI), 2010 International Conference on
  • Conference_Location
    Erode
  • Electronic_ISBN
    978-81-8371-369-6
  • Type

    conf

  • Filename
    5738807