摘要
随着网络攻击行为事件的频繁发生,互联网安全受到人们的持续关注,人们对于网络安全性能也有了更高的要求。网络安全态势分析提升了网络发展趋势,应用遗传算法优化改进BP神经网络权值以此来获取全局最优解,加快了网络收敛速度,并将其应用在训练好的网络安全态势评估模型中,实验结果表明,提出的基于BP神经网络安全态势评估模型中具备较好的训练集以及收敛速度,评估效率也更符合预期值。
With the frequent occurrence of network attack events,Internet security has received continuous attention,and people have higher requirements for network security performance.Network security situation analysis improves the development trend of Internet.The genetic algorithm is used to optimize and improve BP neural network weights,so as to obtain the global optimal solution and speed up network convergence,and then it is applied to the trained network security situation assessment model.The experimental results show that the proposed assessment model based on BP neural network security situation has a better training set and convergence speed,and the evaluation efficiency is also in line with the expected value.
作者
朱敏
ZHU Min(Center for Modern Education technology,Meizhouwan Vocational and Technical College,Putian 351119,China)
出处
《长春大学学报》
2021年第12期6-11,共6页
Journal of Changchun University
基金
福建省2018年中青年教师教育科研项目(JZ181031)。
关键词
安全态势感知
BP神经网络
训练集
security situation awareness
BP neural network
training set
