Main Reference PaperQuantifying Interdependent Privacy Risks with Location Data, IEEE Transactions on Mobile Computing, 2016 [Java].
  • Proposed work quantify the effect of users location privacy on social networks when co location information and individual location information is available. A low complexity of optimal inference algorithm is proposed to protect the localization attack over the social networks.

+ Description
  • Proposed work quantify the effect of users location privacy on social networks when co location information and individual location information is available. A low complexity of optimal inference algorithm is proposed to protect the localization attack over the social networks.

  • To protect the privacy users of social networks from the localization attacks.

  • To mitigate the privacy risks stemming from co-location information.

+ Aim & Objectives
  • To protect the privacy users of social networks from the localization attacks.

  • To mitigate the privacy risks stemming from co-location information.

  • This work may contributed to investigate the case where co locations are not explicitly reported by the users, instead the adversary has access to the social ties between the user.

+ Contribution
  • This work may contributed to investigate the case where co locations are not explicitly reported by the users, instead the adversary has access to the social ties between the user.

  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1 & J2SE.

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

  • Netbeans 8.0.1 & 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.