Privacy Preserving in Social Networks Based on Greedy Perturbation
LIU Hua-ling1,2, ZHENG Jian-guo2, SUN Ci-hai1
1. Business Information Management School, Shanghai University of International Business and Economics, Shanghai 201620, China; 2. Glorious Sun School of Business and Management, Donghua University, Shanghai 201620, China
Abstract:For the privacy preserving problem in the data mining technology of the social networks,weights of the connected edge of the networking and their preserving is very important.We develop a privacy preserving strategy based on data perturbation algorithm.The strategy applies the greedy perturbation algorithm to perturb edge weighs so that the shortest path of the network can be kept,and its length can be similar with that of the original one.The results of simulation calculation show that the perturbation strategy can march with the expected theoretical analysis results.
刘华玲, 郑建国, 孙辞海. 基于贪心扰动的社交网络隐私保护研究[J]. 电子学报, 2013, 41(8): 1586-1591.
LIU Hua-ling, ZHENG Jian-guo, SUN Ci-hai. Privacy Preserving in Social Networks Based on Greedy Perturbation. Chinese Journal of Electronics, 2013, 41(8): 1586-1591.
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