中文摘要：

针对传统免疫模型在时序网络中所面临的难以收集、分析网络拓扑信息的困境，提出了基于随机游走机制的免疫策略，一定数量的免疫粒子被随机地分配到网络节点上，当该节点有边激活时，免疫粒子就可以沿着激活边游走到另一节点，获得免疫粒子的节点获得免疫能力，失去免疫粒子的节点转换成非免疫的易感态。根据随机游走者之间在转移时是否相互影响，分别建立了非独立随机游走免疫模型和P_独立随机游走免疫模型。在这两种免疫模型中，免疫粒子传播所需的网络开销受到事先给定的免疫粒子密度的限制。实验表明，这两种随机游走免疫模型可以获得比熟人免疫模型更好的免疫效果，而与目标免疫模型的比较结果取决于网络拓扑结构的异质性程度。

英文摘要：

For the problems of traditional immune models arising in collectingand analyzing network topology information in temporal networks, an immune strategy based on random walk mechanism is put forward and itcan be implemented withoutcollectingnetwork topology information. A certain number of immune particles were randomly assigned to the network nodes.When a nodewith immune particles has one or more activated links,the immune particles on the node will walk to another node along anactivated link of the node.The nodes with immune particlesacquire the immunity,but thenodes losingimmune particleswill betransformed into the susceptible state. Considering whether the random walkers exert impact upon each other when they move, the dependent random walk immune model and the P_independent random walk immune model are established,respectively, in which the network transmission overhead of the immune particle is limited by a given immune particle density. Experiments show the two random walk immune models are characterized by their better immune effects with lower immune particle density and the network overhead when compared with acquaintances immune model. In addition, the comparative result with the target immune model depends on heterogeneity of network topology.