Betweenness Centrality Based k-Anonymity for Privacy Preserving in Social Networks

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Author(s)
Tian, Hui
Lu, Yue
Liu, Jingtian
Yu, Jingjing
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Haghighi, PD

Salvadori, IL

Steinbauer, M

Khalil, I

AnderstKotsis, G

Date
2018
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Yogyakarta, Indonesia

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Abstract

In order to reduce information loss rate of the k-anonymous network, we propose an anonymous network reconstruction algorithm based on nodes' betweenness centrality. Betweenness centrality measures the nodes' significance in graph based on the shortest paths. In our algorithm, nodes are sorted according to betweenness centrality and the candidate nodes with great value are reconnected preferentially. Then the backbone structure of the network could be retained which guarantee the important features of the reconstruct network. We evaluate our method on real data sets by different metrics. The experiment results justify the efficiency and practical utility of our proposed method.

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Proceedings of the 16th International Conference on Advances in Mobile Computing and Multimedia - MoMM2018

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2018-Nov

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Distributed computing and systems software

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