摘要
频繁发生的网络安全事件带来各类严重威胁,构建网络安全指标体系对掌握宏观的网络安全状态具有重要意义。文章采用基于BP神经网络的网络安全指标体系建模的方式,对网络安全态势进行评估,然后进一步对网络安全指标体系模型进行优化和改良。研究比较不同建模参数下的指标体系构建效果,最终通过比较分析,拟合得到较优BP模型构建方式。
Frequent network security incidents bring various serious threats,and building network security indication-system（ NSIS） is of great significance for mastering the macro network security state. In this paper,the NSIS model based on back propagation neural network is used to evaluate the network security situation,and then the NSIS model is further optimized and improved. The construction effects of indication-system are researched and compared under different modeling parameters. Finally,through comparative analysis,a better BP model construction will be achieved.
作者
刘海天
韩伟红
贾焰
Liu Haitian;Han Weihong;Jia Yan(College of Computer, National University of Defense Technology, Changsha 410073, China;Network Space Advanced Technology Research Institute, Guangzhou University, Guangzhou 510006, China;Guangdong Institute of Electronic Information Engineering, University of Electronic Science and technology of China, Dongguan 523808, China)
出处
《信息技术与网络安全》
2018年第4期26-29,共4页
Information Technology and Network Security
基金
国家重点研发计划(2016YFB0800303)
东莞市引进创新科研团队计划
关键词
BP神经网络
网络安全指标体系
基础运行指数
指标权值
收敛性
网络安全态势
back propagation neural network （BPNN）
network security indication-system（NSIS）
basic operating index
indicator weight
convergence
network security situation
