Simulation of Seismic Network Data Security Situation Awareness Based on Cloud Computing
Before an earthquake occurs,there are special wave response characteristics,and the scope of the earthquake can be determined through the disaster information of the seismic network.However,individual network users are unable to query earthquake data in a timely manner through terminal servers,resulting in delayed perception of earthquake safety.In this paper,a cloud computing based seismic network data security situational awareness meth-od is proposed to address the computationally intensive and complex processing requirements of seismic data process-ing.Bayesian structure was incorporated into the seismic node layout to form a hybrid model for security situation ac-quisition.The data classification method was adopted to estimate seismic situation data and extract the membership characteristics of earthquake,thus constructing a model of seismic network data security situation awareness.Then,the amount of seismic information was calculated according to regional influence factors.Finally,the similarity principle was used to distinguish the disaster degree and thus to detect the safety situation of seismic region.The experimental results show that the displacement between seismic layers sensed by the proposed method is consistent with the epi-center azimuth and actual situation,and the deviation is small,so the method can clarify the current safety situation of seismic region.
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