Main Reference PaperPractical Privacy-Preserving MapReduce Based K-means Clustering over Large-scale Dataset, IEEE Transactions on Cloud Computing, January 2017 [Python].
  • A practical privacy-preserving K-means clustering scheme is proposed that in which the cloud servers perform clustering over encrypted datasets and it is extremely suitable for parallelized processing in cloud computing environment.

Description
  • A practical privacy-preserving K-means clustering scheme is proposed that in which the cloud servers perform clustering over encrypted datasets and it is extremely suitable for parallelized processing in cloud computing environment.

  • To perform clustering with privacy protection.

  • To improve clustering speed and accuracy .

Aim & Objectives
  • To perform clustering with privacy protection.

  • To improve clustering speed and accuracy .

  • Improved K-means clustering technique is applied over the encrypted dataset..

Contribution
  • Improved K-means clustering technique is applied over the encrypted dataset..

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

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