Main Reference PaperPreventing Private Information Inference Attacks on Social Networks, IEEE Transactions on Knowledge and Data Engineering, Aug 2013.
  • This project discovers how to cause inference attacks known social networking data to predict undisclosed private information about individuals. The primary objective of this project is to protect the information inference attack performed over the social networks. Social networks such as Facebook allow it users to share their information about themselves among their friends

+ Description
  • This project discovers how to cause inference attacks known social networking data to predict undisclosed private information about individuals. The primary objective of this project is to protect the information inference attack performed over the social networks. Social networks such as Facebook allow it users to share their information about themselves among their friends

  • To protect the privacy users of social networks from the information inference attack carried out over their released information in the network.

  • To protect privacy using effective sanitization techniques.

  • To provide user customizable anonymity using personalized anonymity.

+ Aim & Objectives
  • To protect the privacy users of social networks from the information inference attack carried out over their released information in the network.

  • To protect privacy using effective sanitization techniques.

  • To provide user customizable anonymity using personalized anonymity.

  • Contributed technique performs the minimum generalization for satisfying everybody’s requirements, and thus, retains the largest amount of information from the microdata. The core of the solution is the concept of personalized anonymity, i.e., a person can specify the degree of privacy protection for her/his sensitive values

+ Contribution
  • Contributed technique performs the minimum generalization for satisfying everybody’s requirements, and thus, retains the largest amount of information from the microdata. The core of the solution is the concept of personalized anonymity, i.e., a person can specify the degree of privacy protection for her/his sensitive values

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1 and J2SE

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

  • Netbeans 8.0.1 and J2SE

  • 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.