(untitled) (International Journal of Engineering and Computer Science, 2015)
In our modern life, social networks are pervasive and omnipresent. Activities like tweeting, uploading photos on Facebook, finding job by using LinkedIn, are nothing but the use of social networks. Even the average computers are used to social networks. The incredible use of social networks in counter-terrorism and marketing has increased the need for accurate classification techniques for hiding important data and connections. However, users of admissible social networks have reasonable concerns about the use of their private data. Also, nowadays many social networks that have been partly driven by Web 2.0 applications have made publicly availability of the data. This data is analyzed in many different ways. Publishing the social network data by maintaining the privacy is a task of concern. In this paper, we present a brief review of the existing techniques for privacy preserving publishing of social network data.