Main Reference PaperA privacy-preserving mobile application recommender system based on trust evaluation, Journal of computational science, 2018 [Java]
  • This work presents two privacy-preserving mobile app recommendation schemes by analyzing the user trust behaviors in the mobile application. By applying the homomorphic encryption and the proposed security protocols, it preserved the user data in two different scenarios including a centralized cloud service and distributed social networking.

Description
  • This work presents two privacy-preserving mobile app recommendation schemes by analyzing the user trust behaviors in the mobile application. By applying the homomorphic encryption and the proposed security protocols, it preserved the user data in two different scenarios including a centralized cloud service and distributed social networking.

  • To preserve the mobile user data based on trust behaviors.

  • To ensure the security and privacy of the mobile application recommendation

Aim & Objectives
  • To preserve the mobile user data based on trust behaviors.

  • To ensure the security and privacy of the mobile application recommendation

  • This work focuses on identifying internal malicious users through intelligent learning while evaluating user trust behaviors.

Contribution
  • This work focuses on identifying internal malicious users through intelligent learning while evaluating user trust behaviors.

  • Operating system: Ubuntu / Windows

  • Language: Java

Software Tools & Technologies
  • Operating system: Ubuntu / Windows

  • Language: Java

  • 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.

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

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