摘要
信息系统风险评估是保证信息系统安全的关键技术。针对当前信息系统风险评估过程存在的局限性,为了提高信息系统风险评估的准确性,加快信息系统风险评估的速度,设计了一个基于因子分析和神经网络的信息系统风险评估模型。首先根据科学、全面原则设计信息系统风险指标,并对指标进行选择操作,选出重要的信息系统风险评估指标,最后采用RBF神经网络分析和挖掘指标和风险等之间联系,设计了理想的信息系统风险评估模型,在MATLAB 2018平台上风险评估测试实验,测试结果说明因子分析和神经网络可以描述信息系统风险变化趋势,提升信息系统风险评估准确性,而且评估耗费时间缩短,解决了当前信息系统风险评估过程存在的不足,具有更高的实际应用价值。
Information system risk assessment is a key technology to ensure the security of information system.In view of various limitations in the current information system risk assessment process,in order to improve the accuracy of information system risk assessment and speed up the information system risk assessment,an information system risk assessment model based on factor analysis and neural network is designed.Firstly,information system risk indicators are designed according to the scientific and comprehensive principles,and the indicators are selected to screen important information system risk assessment indicators.Finally,the RBF neural network is used to analyze and mine the relationship between indicators and risks,and an ideal information system risk assessment model is designed.The risk assessment test experiment is carried out on the MATLAB 2018 platform.Factor analysis and neural network can describe the change trend of information system risk,improve the accuracy of information system risk assessment and shorten the assessment time,which solves the shortcomings of the current information system risk assessment process,and has higher practical application value.
作者
胥林
XU Lin(Information Management Center, SINOPEC Shengli Oilfield Company, Dongying 257000, China)
出处
《微型电脑应用》
2022年第2期153-155,168,共4页
Microcomputer Applications
