Comprehensive Degree Based Key Node Recognition Method in Complex Networks
AffiliationSchool of Information, University of Arizona
MetadataShow full item record
PublisherSpringer International Publishing
CitationXie, L., Sun, H., Yang, H., & Zhang, L. (2021). Comprehensive Degree Based Key Node Recognition Method in Complex Networks. International Conference on Information and Communications Security 2021.
Rights© Springer Nature Switzerland AG 2021.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractAiming at the problem of the insufficient resolution and accuracy of the key node recognition methods in complex networks, a Comprehensive Degree Based Key Node Recognition Method (CDKNR) in complex networks is proposed. Firstly, the K-shell method is adopted to layer the network and obtain the K-shell (Ks) value of each node, and the influence of the global structure of the network is measured by the Ks value. Secondly, the concept of Comprehensive Degree (CD) is proposed, and a dynamically adjustable influence coefficient μi is set, and the Comprehensive Degree of each node is obtained by measuring the influence of the local structure of the network through the number of neighboring nodes and sub-neighboring nodes and influence coefficient μi. Finally, the importance of nodes is distinguished according to the Comprehensive Degree. Compared with several classical methods and risk assessment method, the experimental results show that the proposed method can effectively identify the key nodes, and has high accuracy and resolution in different complex networks. In addition, the CDKNR can provide a basis for risk assessment of network nodes, important node protection and risk disposal priority ranking of nodes in the network.
Note12 month embargo; first online: 17 September 2021
VersionFinal accepted manuscript