A new method for the prediction of network security situations based on recurrent neural network with gated recurrent unit

作     者：Wei Feng Yuqin Wu Yexian Fan 

作者机构：Department of Computer ScienceCollege of Information and Electrical EngineeringNingde Normal UniversityNingdeChina College of Information and Electrical EngineeringNingde Normal UniversityNingdeChina 

出 版 物：《International Journal of Intelligent Computing and Cybernetics》 (智能计算与控制论国际期刊（英文）)

年 卷 期：2020年第13卷第1期

页      面：25-39页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：supported by the funds of Ningde Normal University Youth Teacher Research Program(2015Q15) The Education Science Project of the Junior Teacher in the Education Department of Fujian province(JAT160532) 

主　　题：Gated recurrent unit Internal and external information features Network security situation Recurrent neural network Time-series data processing 

摘      要：Purpose-The purpose of this paper is to solve the shortage of the existing methods for the prediction of network security situations(NSS).Because the conventional methods for the prediction of NSS,such as support vector machine,particle swarm optimization,etc.,lack accuracy,robustness and efficiency,in this study,the authors propose a new method for the prediction of NSS based on recurrent neural network(RNN)with gated recurrent ***/methodology/approach-This method extracts internal and external information features from the original time-series network data for the first ***,the extracted features are applied to the deep RNN model for training and *** iteration and optimization,the accuracy of predictions of NSS will be obtained by the well-trained model,and the model is robust for the unstable network ***-Experiments on bench marked data set show that the proposed method obtains more accurate and robust prediction results than conventional *** the deep RNN models need more time consumption for training,they guarantee the accuracy and robustness of prediction in return for ***/value-In the prediction of NSS time-series data,the proposed internal and external information features are well described the original data,and the employment of deep RNN model will outperform the state-of-the-arts models.