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A New Approach to Supervise Security in Social Network through Quantum Cryptography and Non- Linear Dimension Reduction Techniques

Social networking sites such as Orkut, Tribe, or Facebook allow millions of individuals to create online profiles and share personal information with vast networks of friends and, often, unknown numbers of strangers. Some of the information revealed inside these networks is private and it is possible that corporations could use learning algorithms on the released data to predict undisclosed private information. To find the patterns of information revelation and their security implications, we analyze the online behavior of wiki-vote data set and evaluate the amount of information they disclose and study their dimension used for reduction. In this paper we conclude that dimension reduction is one of the factors through we can achieve the security and maintain the integrity of dataset. We highlight various Non-Linear dimension reduction techniques with quantum cryptography to produce the desire result and show the comparative result with linear dimension