4.2 Article

Identifying important nodes affecting network security in complex networks

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/1550147721999285

关键词

Network security; complex network; node importance ranking; K-shell algorithm; structural hole

资金

  1. National Natural Science Foundation of China [61972334, 61772449]
  2. Natural Science Foundation of Hebei Province, China [F2017203019]

向作者/读者索取更多资源

An important node identification algorithm based on an improved structural hole and K-shell decomposition algorithm is proposed to identify important nodes that affect security in complex networks. By considering the global structure of a network and proposing a network security evaluation index of important nodes, combined with node information control ability index, the algorithm ranks the importance of nodes and analyzes their influence on network security and their own propagation ability. Experimental results show that the proposed algorithm can improve the accuracy of important node identification, with applications in monitoring network security.
An important node identification algorithm based on an improved structural hole and K-shell decomposition algorithm is proposed to identify important nodes that affect security in complex networks. We consider the global structure of a network and propose a network security evaluation index of important nodes that is free of prior knowledge of network organization based on the degree of nodes and nearest neighborhood information. A node information control ability index is proposed according to the structural hole characteristics of nodes. An algorithm ranks the importance of nodes based on the above two indices and the nodes' local propagation ability. The influence of nodes on network security and their own propagation ability are analyzed by experiments through the evaluation indices of network efficiency, network maximum connectivity coefficient, and Kendall coefficient. Experimental results show that the proposed algorithm can improve the accuracy of important node identification; this analysis has applications in monitoring network security.

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