Main Reference PaperService-Oriented Architecture for High-Dimensional Private Data Mashup, IEEE Transactions on Service Computing, 2012
  • This project allows different service providers to flexibly integrate their expertise and to deliver highly customizable services to their customers through the mashup technology. This project deals with resolve a privacy problem in a real-life mashup application for theonline advertising industry in social networks, and propose a service-oriented architecture along with a privacy-preserving data mashup algorithm to address the aforementioned challenges

+ Description
  • This project allows different service providers to flexibly integrate their expertise and to deliver highly customizable services to their customers through the mashup technology. This project deals with resolve a privacy problem in a real-life mashup application for theonline advertising industry in social networks, and propose a service-oriented architecture along with a privacy-preserving data mashup algorithm to address the aforementioned challenges

  • To curse of high dimensionality,

  • To avoid useless data analysis.

  • To preserving both privacy and information utility on the mashup data.

  • To illustrate the impacts for achieving LKC-privacy with respect to classification analysis and general data analysis.

+ Aim & Objectives
  • To curse of high dimensionality,

  • To avoid useless data analysis.

  • To preserving both privacy and information utility on the mashup data.

  • To illustrate the impacts for achieving LKC-privacy with respect to classification analysis and general data analysis.

  • The contribution method implements data mashup application for the online advertising industry in social networks, and generalize their privacy and information requirements to the problem of privacy-preserving data mashup for the purpose of joint data analysis on the high-dimensional data PHDMashup achieves a broad range of LKC-privacy requirements without significantly sacrificing the information utility.

+ Contribution
  • The contribution method implements data mashup application for the online advertising industry in social networks, and generalize their privacy and information requirements to the problem of privacy-preserving data mashup for the purpose of joint data analysis on the high-dimensional data PHDMashup achieves a broad range of LKC-privacy requirements without significantly sacrificing the information utility.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2EE

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

  • Netbeans 8.0.1, J2EE

  • B.E / B.Tech / M.E / M.Tech

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

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