刘振鹏;王烁;贺玉鹏;李小菲;
LIU Zhen-peng;WANG Shuo;HE Yu-peng;LI Xiao-fei;School of Cyber Security and Computer, Hebei University;Center for Information Technology, Hebei University;

• 1:河北大学网络空间安全与计算机学院
• 2:河北大学信息技术中心

摘要(Abstract)：

针对当前社会网络的动态更新速度越来越快,而社会网络中差分隐私保护方法迭代速度慢的问题,提出一种基于B+树索引的动态社会网络差分隐私保护方法.使用B+树索引社会网络图的边,根据差分隐私并行性组合的特点,对B+树的索引数据划分,为数据分配不同的ε并添加拉普拉斯噪声,实现数据隐私后的整体高效用性和局部强保护性;在迭代时利用B+树的高效索引对欲更新的信息快速定位,实现动态社会网络差分隐私保护的快速迭代.实验表明,B+树索引有效提高了动态社会网络差分隐私保护的迭代速度,同时差分隐私的并行性提高了数据的效用性.
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.

关键词(KeyWords)： 动态社会网络;差分隐私;B+树;迭代速度;并行性
dynamic social network;differential privacy;B+ tree;iteration speed;parallelism

Abstract:

Keywords:

基金项目(Foundation): 河北省自然科学基金(F2019201427);; 教育部“云数融合科教创新”基金(2017A20004)

作者(Author): 刘振鹏;王烁;贺玉鹏;李小菲;
LIU Zhen-peng;WANG Shuo;HE Yu-peng;LI Xiao-fei;School of Cyber Security and Computer, Hebei University;Center for Information Technology, Hebei University;

Email:

DOI:

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