具有二次预警行为的复杂网络病毒传播分析

Analysis of Complex Network Virus Propagation with Secondary Warning

社会网络中,健康节点获得病毒正在蔓延的消息,会转化为预警节点,这种行为称为预警行为,感染节点存在一定的概率转化为预警节点,将此行为称为二次预警行为。据此提出了一种具有二次预警行为的SAIS(susceptible-alert-infec-ted-susceptible)模型。从微分动力学系统角度分析病毒传播的临界值特性,并与具有一次预警行为的SAIS传播模型进行比较,通过模拟仿真对结论进行验证。研究结果表明,具有二次预警行为的SAIS模型的稳态感染节点密度小于具有一次预警行为的SAIS模型的稳态感染节点密度,具有二次预警行为的SAIS模型的病毒传播阈值大于具有一次预警行为的SAIS模型的病毒传播阈值。研究还发现,随着二次预警率的增加,稳态感染节点密度不断减小,从而可以减少病毒爆发规模,减缓病毒在网络中的爆发。

In social networks,when susceptible individuals find that the virus is spreading,they will be transformed into alert individuals,which is called early warning behavior.Infected individuals have a certain probability to be transformed into alert individuals,which is called secondary early warning behavior.Therefore,we propose a susceptible-alert-infected-susceptible(SAIS)model with secondary early warning behavior.We analyze the critical value characteristics of virus propagation from the perspective of differential dynamics system,and compare with SAIS model with one warning behavior.The conclusion is verified by simulation.The study shows that the steady-state infection individuals density of SAIS model with secondary early warning behavior is lower than that of SAIS with primary early warning behavior,and the former has a larger virus propagation threshold than the latter.At the same time,it is also found that with the increase of the secondary warning rate,the density of steady-state infected individuals keeps decreasing,which can reduce the scale of virus outbreak and slow down the outbreak of virus in the network.