• DocumentCode
    3039033
  • Title

    Preserving Privacy in MapReduce Based Clouds: Insight into Frameworks and Approaches

  • Author

    Al-Aqeeli, Shaden ; Alnifie, Ghada

  • Author_Institution
    Dept. of Comput. Sci., King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2015
  • fDate
    26-29 April 2015
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    The massive increase in computational power and data storage capacity provided by Cloud Computing as well as the vast amount of data generated each day have provided many organizations, businesses and authorities with more opportunities due to the advancement in data analysis and mining techniques. A serious problem is that Big Data includes sensitive user information that cannot be released to the cloud without proper protection because of multi-tenancy issues and threats. Privacy preservation of big data has been under intensive investigation with many different approaches proposed. In this paper, we focus on the research challenges of the privacy-preserving problem in the context of cloud computing and we survey existing solution approaches. Furthermore, a review of different existing MapReduce based frameworks will be presented and investigated against the research challenges identified in this paper.
  • Keywords
    Big Data; cloud computing; data analysis; data mining; data privacy; Big Data privacy preservation; MapReduce based cloud computing; data analysis; data mining techniques; multitenancy issues; Big data; Cloud computing; Computational modeling; Data privacy; Organizations; Privacy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (ICCC), 2015 International Conference on
  • Conference_Location
    Riyadh
  • Print_ISBN
    978-1-4673-6617-5
  • Type

    conf

  • DOI
    10.1109/CLOUDCOMP.2015.7149652
  • Filename
    7149652