%0 Journal Article %A ZHANG Xiaolin %A YU Fangming %A HE Xiaoyu %A YUAN Haochen %T Distributed dynamic social network privacy-preserving method based on link prediction %D 2018 %R 10.3778/j.issn.1002-8331.1708-0394 %J Computer Engineering and Applications %P 85-91 %V 54 %N 22 %X Aiming at the low implementation efficiency and poor availability of data published in dynamic social network as well as processing large-scale dynamic social network graphs in a stand-alone workstation environment, this paper proposes a Distributed Dynamic Social Network Privacy-Preserving method Based on Link Prediction(D-DSNBLP). This method realizes the parallel processing of anonymous large-scale graph data by the iterative updating model of message in Pregel-like. Firstly, the node is grouped by fast iteration. Secondly, the candidate node set is constructed in parallel according to the node attribute value in each group. Finally, a mutex set is built to add edges, to protect the privacy of nodes. Experiments show that the D-DSNBLP method improves the efficiency of processing large-scale dynamic social network and ensures the data availability of anonymous graphs. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1708-0394