Information Security Evaluation based on Artificial Neural Network

Wang Lin, Tian Bing, Li Yan, Qu Yan-sheng
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引用次数: 2

Abstract

In order to improve the information security ability of the network information platform, an information security evaluation method is proposed based on artificial neural networks. Based on the comprehensive analysis of the security events in the construction of the network information platform, the risk assessment model of the network information platform is constructed based on the artificial neural network theory. The weight calculation algorithm of artificial neural networks and the minimum artificial neural network pruning algorithm are also given, which can realize the quantitative evaluation of network information security. The fuzzy neural network weighted control method is used to control the information security, and the non-recursive traversal method is adopted to realize the adaptive training of the information security assessment process. The adaptive learning of the artificial neural network is carried out according, and the ability of information encryption and transmission is improved. The information security assessment is realized. The simulation results show that the method is accurate, and the information security is ensured.
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基于人工神经网络的信息安全评估
为了提高网络信息平台的信息安全能力,提出了一种基于人工神经网络的信息安全评估方法。在对网络信息平台建设中的安全事件进行综合分析的基础上,基于人工神经网络理论构建了网络信息平台风险评估模型。给出了人工神经网络的权值计算算法和最小人工神经网络剪枝算法,实现了对网络信息安全的定量评价。采用模糊神经网络加权控制方法对信息安全进行控制,采用非递归遍历方法实现信息安全评估过程的自适应训练。据此对人工神经网络进行自适应学习,提高了信息加密和传输的能力。实现了信息安全评估。仿真结果表明,该方法是准确的,保证了信息的安全性。
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来源期刊
International Journal of Performability Engineering
International Journal of Performability Engineering Engineering-Safety, Risk, Reliability and Quality
CiteScore
2.30
自引率
0.00%
发文量
56
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