关键词: 传染病模型, 谣言溯源, 信息安全, 社交网络

Abstract: 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.

Key words: infection disease model, rumor source detection, information security, social network