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基于改进BP神经网络的电子政务内网信息安全评估方法
引用本文:何文才,张川,叶思水,贾新会,刘培鹤.基于改进BP神经网络的电子政务内网信息安全评估方法[J].网络安全技术与应用,2014(5):174-177.
作者姓名:何文才  张川  叶思水  贾新会  刘培鹤
作者单位:北京电子科技学院,北京100070
基金项目:本文受“中央高校基本科研业务费资助(项目编号:2014CLJH05)”.
摘    要:为了发现电子政务内网的信息安全隐患,提出一种采用改进反向传播人工神经网络(BP ANN)技术的电子政务内网信息安全的评估方法,基于改进BP ANN建立电子政务内网神经网络评估模型.以电子政务内网主要信息安全指标作为训练样本,对建立的BP ANN评估模型进行学习和训练,找到输入与输出之间的关系,并用样本对训练好的BP网络进行验证.仿真结果表明,评估方法能够较好的为复杂的电子政务内网进行信息安全评估,评估模型稳定且自适应性强.

关 键 词:BP神经网络  电子政务内网  信息安全  安全评估

Approach of information security assessment for Electronic Government network based on improved BP model of artificial neural network
He Wencai,ZhangChuan,Ye Sishui,JiaXinhui,LiuPeihe.Approach of information security assessment for Electronic Government network based on improved BP model of artificial neural network[J].Net Security Technologies and Application,2014(5):174-177.
Authors:He Wencai  ZhangChuan  Ye Sishui  JiaXinhui  LiuPeihe
Affiliation:He Wencai, ZhangChuan, Ye Sishui, JiaXinhui, LiuPeihe
Abstract:For the purpose of finding E-government network's hidden danger.An evaluation model was proposed by using a artificial neural network ( ANN ) based on improved BP model.The major information security indicators of E-government network were used as the training samples, which were adapted to find the intrinsic links between the input and output by learning and training process.An experiment was conducted by using the well-trained ANN network to evaluate the security of E-government network.The experimental results show that the proposed ANN evaluation model can apply to evaluate E-government network's information security.It is highly adaptive and stabilized.
Keywords:Back propagation neural network  Electronic Government  information security  security assessment
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