Gao Chao, Liu Jiming, Zhong Ning
1International WIC Institute, Beijing University of Technology, 100124 Beijing, China.
Beijing Key Laboratory of Multimedia and Intelligent Software, 100124 Beijing, China.
Knowl Inf Syst. 2011;27(2):253-279. doi: 10.1007/s10115-010-0321-0. Epub 2010 Jul 14.
Network immunization strategies have emerged as possible solutions to the challenges of virus propagation. In this paper, an existing interactive model is introduced and then improved in order to better characterize the way a virus spreads in email networks with different topologies. The model is used to demonstrate the effects of a number of key factors, notably nodes' degree and betweenness. Experiments are then performed to examine how the structure of a network and human dynamics affects virus propagation. The experimental results have revealed that a virus spreads in two distinct phases and shown that the most efficient immunization strategy is the node-betweenness strategy. Moreover, those results have also explained why old virus can survive in networks nowadays from the aspects of human dynamics.
网络免疫策略已成为应对病毒传播挑战的可能解决方案。本文引入并改进了一个现有的交互模型，以便更好地描述病毒在具有不同拓扑结构的电子邮件网络中的传播方式。该模型用于展示一些关键因素的影响，特别是节点的度和介数。然后进行实验，以研究网络结构和人类动态如何影响病毒传播。实验结果表明，病毒以两个不同阶段传播，并表明最有效的免疫策略是节点介数策略。此外，这些结果还从人类动态的角度解释了为什么旧病毒如今仍能在网络中存活。
