Abstract
In complex networks, the security of real community is low. Besides, the structure of community network is hierarchical and overlapped. Therefore, the community network cannot divide the secure structure accurately. To address this issue, this work presents a hierarchical community detection algorithm. Firstly, a secure community clustering model is built. On the basis of the hierarchical structure, the bridge joint between communities can be found. After that, the secure clustering is performed. Finally, the community is detected based on the hierarchical and overlapped features. The experiments show that, the proposed algorithm has improved the computation speed. The detected complex network community has obvious structure. Besides, the security performance in probability of coincidence is encouraging.
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