Privacy Preservation Techniques for Social Networks Users

On the internet, Online Social Networks (OSNs) have become a popular service. It's completely changing the way people engage with one another. The latent information in social networks data presents interesting data mining and information extraction challenges. As a result, it is necessary to publish data from social media platforms, but this has resulted in the possibility of sensitive and confidential information about individuals being leaked. This necessitates the protection of privacy prior to the dissemination of data from such networks. In recent years, protecting the privacy of data from Online Social Networks has become a top priority. Several academic research have presented ways for protecting micro-data and social network data privacy. The strategies that secure data privacy are the focus of the literature review paper. Its objective is to help people realize the implications of maintaining their privacy. Then, as a protype model an experiment has been conducted by using ARX tool to preserve the privacy of users by considering the data of real-time social network CORA. It has been analyzed that K-anonymity is able to preserve the privacy of users in CORA dataset. The risk of compromising the privacy has been reduced by a factor of 1.6.