Dynamic social network differential privacy protection based on B+ tree index

Abstract

Abstract: The dynamic updating speed of social network is getting faster and faster. Aiming at the slow iteration speed of differential privacy protection methods in current social network, a differential privacy protection method of dynamic social network based on B+ tree index is proposed. By using the edge of B+ tree index social network graph, according to the characteristics of differential privacy parallelism combination, the index data of B+ tree are divided, and the data are assigned with different epsilon and epsilon ratios and added with Laplace noise, so as to achieve the overall high efficiency and strong local protection after data privacy. During the iteration, the efficient index of B+ tree is used to quickly locate the information to be updated, so as to realize the rapid iteration of differential privacy protection of dynamic social network. Experiments show that the B+ tree index effectively improves the iteration speed of differential privacy protection in dynamic social networks, and the parallelism of differential privacy improves the utility of data. This method effectively solves the problem of slow iteration of differential privacy protection in social networks.

Key words: dynamic social network, differential privacy, B+ tree, iteration speed, parallelism

CLC Number:

TP399

LIU Zhen-peng, WANG Shuo, HE Yu-peng, LI Xiao-fei. Dynamic social network differential privacy protection based on B+ tree index[J]. Journal of Lanzhou University of Technology, 2020, 46(6): 98-103.

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