基于扩展传染病模型的谣言溯源

Rumor Source Detection Based on Extended Epidemic Model

为了更加贴合实际情况研究谣言溯源问题,考虑社交网络中对传播谣言节点的封禁隔离能力,扩展经典SIR传染病模型提出SIOR(Susceptible-Infected-isOlated-Removed)模型。基于最优信息传播过程计算出谣言源的估计值,并且针对SIOR模型验证该估计值近似于网络拓扑中的Jordan感染中心。根据RI(Reverse Infection)算法,提出一种针对SIOR模型的反向信息传播算法,该算法可以识别出网络拓扑图中的Jordan感染中心。最后在不同的网络中模拟实验,验证该算法的溯源效率比传统的溯源算法更优,此外,与SIR模型下溯源对比,SIOR模型溯源的准确性有所提高。

In order to study the issue of rumors detection of better fitting the actual situation,this paper considers the ability of banning and isolating nodes that spread rumors in social networks,proposes a new model called SIOR(Susceptible-Infected-isOlated-Removed),which is based on the classic model called SIR.Then this paper obtains the source estimator through the optimal information propagation process and verifies that the estimated value is similar to the Jordan Infection Center in the network topology based on the SIOR model.Finally,this paper proposes a reverse infection propagation algorithm for the SIOR model,which can identify the Jordan infection center in the network topology,then compares the algorithm with other centrality detection algorithms through simulation experiments to verify the feasibility of the estimator.In addition,the accuracy under SIOR model is improved compared with SIR model.