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
  • Privacy for the large set of data in the cloud such is made possible using the two-phase top-down specialization approach in which Map-Reduce framework is used to achieve scalability and efficiency in terms of anonymization.

+ Description
  • Privacy for the large set of data in the cloud such is made possible using the two-phase top-down specialization approach in which Map-Reduce framework is used to achieve scalability and efficiency in terms of anonymization.

  • 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)

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.