Anonymization Algorithm for Security and Confidentiality of Health Data Set across Social Network

In this paper we propose a social network anonymization algorithm for security and confidentiality of health data set transmitted and shared across a social network. The growing need to address privacy concerns when social network data is released for mining purposes has recently led to considerable interest in various techniques anonymization. In the proposed scheme, the data owners interact over Internet using social network application where the algorithm determines records that can't be disclosed and satisfy a formal privacy protection. Furthermore, this algorithm integrates a secure encryption function, thus, the anonymization health data set is guaranteed during the session. Finally, we present an evaluation under mathematical analysis to prove the correctness of the anonymity function in the algorithm.