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

    Author(s)
    Tian, Hui
    Lu, Yue
    Liu, Jingtian
    Yu, Jingjing
    Griffith University Author(s)
    Tian, Hui
    Year published
    2018
    Metadata
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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 ...
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    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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    Conference Title
    Proceedings of the 16th International Conference on Advances in Mobile Computing and Multimedia - MoMM2018
    Volume
    2018-Nov
    DOI
    https://doi.org/10.1145/3282353.3282366
    Subject
    Distributed computing and systems software
    Publication URI
    http://hdl.handle.net/10072/385799
    Collection
    • Conference outputs

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