Main Reference PaperA Scalable Two-Phase Top-Down Specialization Approach for Data Anonymization Using MapReduce on Cloud, IEEE Transactions on Parallel and Distributed Systems, 2013
  • This paper proposes a scalable two-phase top-down specialization (TDS) approach to anonymize large-scale data sets using the MapReduce framework on cloud. In both phases of the approach, it deliberately designs a group of innovative MapReduce jobs to concretely accomplish the specialization computation in a highly scalable way. Experimental evaluation results demonstrate that with this approach, the scalability and efficiency of TDS can be significantly improved over existing approaches.

+ Description
  • This paper proposes a scalable two-phase top-down specialization (TDS) approach to anonymize large-scale data sets using the MapReduce framework on cloud. In both phases of the approach, it deliberately designs a group of innovative MapReduce jobs to concretely accomplish the specialization computation in a highly scalable way. Experimental evaluation results demonstrate that with this approach, the scalability and efficiency of TDS can be significantly improved over existing approaches.

  • To preserve the privacy of users using k-Anonymity

  • To achieve scalability by effectively managing large set of data

+ Aim & Objectives
  • To preserve the privacy of users using k-Anonymity

  • To achieve scalability by effectively managing large set of data

  • Bottom up approach generalization is contributed for data anonymization in which data Generalization hierarchy is utilized for anonymization.

+ Contribution
  • Bottom up approach generalization is contributed for data anonymization in which data Generalization hierarchy is utilized for anonymization.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2SE, (Cloudsim 3.0.3)

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2SE, (Cloudsim 3.0.3)

  • 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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