尽管计算机病毒与流行病学中的病毒存在很多类似特征，早期研究者也确实从流行病学的模型角度来研究计算机病毒模型，但与流行病学中的病毒相比，计算机病毒实际存在诸多不同之处。本项目围绕基于交通流量的因特网病毒扩散动力学行为开展工作，力图将迅速发展的复杂网络传播动力学理论应用于因特网病毒传播、扩散以及免疫等机制研究，从而实现面向因特网计算机病毒防疫的源头创新。具体研究工作包括：建立病毒传播率，平均发包率固定为常数或非线性变化下基于交通流量的基础模型，分析病毒扩散动力学行为，并将传播动力学对象扩展至谣言，故障或者单纯网路数据等信息主体，以此给出因特网中高鲁棒性容侵容错路由算法。研究适用于因特网计算机病毒扩散模型的免疫算法。给出基于交通流量的病毒扩散动力学模型中最关键节点的评价标准。此外，结合课题组之前在符号向量动力学方面已有原创性积累，给出复杂网络病毒扩散的等价的符号向量动力系统，从而降低分析难度。

Although the computer virus has much in common with the epidemiology and earlier researches also studied the computer virus model through epidemiology, the two are in fact different. This project centers about the research of dynamical behavior of epidemic spreading with traffic flow in the Internet, and tries to apply the rapid-developing dynamical theory of complex network to the study of epidemic spreading, immunization and so on in the Internet, in order to realize the innovation of immunization in Internet virus. In this paper, we build basic SI, SIS and SIR models based on traffic flow with prevalence, constant delivery rate and non-linear variation, and analyze the dynamical behavior of the epidemic spreading. We also study the immunization applied to the Internet epidemic spreading, and provide evaluation criteria of the key node in dynamical epidemic spreading with traffic flow. Moreover, combining with the existing original accumulation we acquired in symbolic vector dynamics before, we provide the equivalent symbolic vector dynamical system of epidemic spreading in complex network, and thus reduce the difficulty of analysis.