PREDICTION MODEL OF SMART NETWORK SECURITY ALARM EVENT DURATION BASED ON SURVIVAL ANALYSIS
To solve the problem that the current smart electric network security prediction system is not sufficiently interpreted,an improved model based on the DeepSurv model in survival analysis is proposed to predict the duration of network security alarm events.In order to speed up the operation speed,the neural network part of the original DeepSurv is improved.Based on K-means,a dimensionality reduction algorithm was proposed to reduce the input data.Through the improved DeepSurv,the survival function of the duration of the smart electric network security alarm event was obtained,and the C-index and MAPE were calculated on this basis.By comparing the model with the original DeepSurv in terms of total time consuming,C-index and MAPE,it is found that the model significantly improved the operation speed while the prediction accuracy was not much different.In addition,as the model is based on survival analysis,it has strong explanatory power and can provide the survival function of network security alarm event on duration,namely,probability prediction on duration,which is of great reference significance for the research of smart electric network security risk prediction.
Smart electric networkNetwork security alarm eventsSurvival analysisNeural networkPrediction of duration
国家科技期刊平台
NSTL
万方数据
维普
