SIRI模型下的网络传染源识别
Network infection source identification under the SIRI model
摘要：
研究了在可恢复-感染-恢复-感染（SIRI）模型下网络中单个感染源的识别问题。我们描述的感染模型，通过状态空间模型，并利用状态传播的方法，我们推导出一个算法称为异构感染传播源（HISS）估计，推断感染源。HISS估计器使用节点状态在特定时间的观测值，其中从感染开始经过的时间是未知的。它能够合并边信息（如果有的话）的观察到的状态的一个子集的节点在不同的时间，和每个感染或恢复节点的先验概率是感染源。仿真结果表明，HISS估计优于动态消息传递和约旦中心估计在很宽的范围内的感染率和再感染率。
英文摘要：
We study the problem of identifying a single infection source in a network under the susceptible-infected-recovered-infected (SIRI) model. We describe the infection model via a state-space model, and utilizing a state propagation approach, we derive an algorithm known as the heterogeneous infection spreading source (HISS) estimator, to infer the infection source. The HISS estimator uses the observations of node states at a particular time, where the elapsed time from the start of the infection is unknown. It is able to incorporate side information (if any) of the observed states of a subset of nodes at different times, and of the prior probability of each infected or recovered node to be the infection source. Simulation results suggest that the HISS estimator outperforms the dynamic message pass- ing and Jordan center estimators over a wide range of infection and reinfection rates.
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