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Dynamic social networks also suffer from privacy violation due to the continuous release of data. In order to defend against enemy attacks, a new dynamic privacy-preserving method is innovated, called Dynamic  k w Re-Structured Diversity Anonymity ( k w -SDA). This method limits the probability of disclosure of node/community identities to  1 / k when data are continuously published by protecting individuals in groups. The graph based on the previous  w − 1 is released, missing some graph alterations. The advantage of the proposed method is to save many features of the network while protecting privacy efficiently and effectively.

Building Security Mechanisms for Cross-Border Business Customer Data Analysis Based on Smart Computing