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Identifying influential nodes in complex networks for network immunization

journal contribution
posted on 2014-10-15, 00:00 authored by L Zhong, C Gao, Zili ZhangZili Zhang, N Shi, J Huang
Identifying influential nodes is of theoretical significance in network immunization which is one of important methods to prevent virus propagation through protecting the influential nodes in a network. Lots of methods have been proposed to find these influential nodes based on the topological characteristics of a network (e.g., degree, betweenness or K-shell). Whereas due to the diversity of network topologies, these methods are not always effective in identifying influential nodes in any benchmark networks. We combine the advantages of existing methods based on attribute ranking and propose a universal ranking method, namely MAF (Multiple Attribute Fusion), to identify influential nodes from a complex network. We compare the efficiency of our proposed method with existing immunization strategies in different types of networks. Simulation results in the interactive email model show that the immunized nodes selected by MAF can restrain virus propagation effectively.

History

Journal

Journal of Computational Information Systems

Volume

10

Issue

20

Pagination

8767 - 8774

Publisher

Binary Information Press

Location

CT, United States

ISSN

1553-9105

Language

eng

Publication classification

C Journal article; C1 Refereed article in a scholarly journal

Copyright notice

2014, Binary Information Press

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