Online social networking sites, like Facebook and Google+, provides a new communication service for online users to stay in contact. With this service, user can share any kind of information with their friends and family over internet. Such communication among user generates the huge amount of data on social networking sites. But with this facility, question is arises regarding mining useful knowledge from such huge amount of data. The analysis of such data will be used in various applications for identification of potential users and promotion of items according to the user interest. From another point of view, online users of such sites often want to make new friends, so the need of good friend recommendation system is arises. It will be helpful to online users to increase the social connections and sharing of information. Old friend recommendation system makes use of users profile for recommendation purpose. But such methods are not reliable if the user wants privacy of their profiles. So another need is arises for privacy preserving friend recommendation approach based on the security of user profiles. Such methods achieve the privacy of personal information of users like friend list. In this paper, we present the comparative survey of recent privacy preserving friend recommendation system based on their advantages and limitations.