User Intended Privacy Preserving Models in Online Social Networks

Abstract

The proposed system introduces new social network privacy management models and it measures their human effects. Here it introduces a mechanism using clustering techniques which helps users to group their friends using policy management. Then it introduces new privacy management model which will give policies to other friends to find similar friends in the network. And thereby explored various ways that help users to find example friends. In addition, it will help to find privacy management models which can be further enhanced and also it helps to detect privacy sentiment of user. Assistant friend grouping will be done for effective friendship establishment. In a network user privacy will be maintained by setting privacy techniques. Privacy management models can be routinely customized to the privacy sentiment and done according to the needs of the user.