摘要
为解决计算机网络在安全管理环节存在的监管滞后、风险频发等问题,规避计算机网络遭受攻击后可能产生的各种损失、危害,保障计算机网络系统的平稳运行,引入机器学习算法进行设计优化。文中首先介绍了研究背景,指出了现阶段计算机网络主要面临数据泄露风险、DDoS攻击风险等,在此基础上依托机器学习算法设计了优化后计算机网络安全管理架构,并梳理了关键技术手段,最后借助仿真平台运行测试。研究结果证明,基于机器学习的计算机网络安全管理技术运行良好,能够较为精准地识别潜在风险,保证计算机网络的安全。
In order to solve the problems of supervision lag and frequent risks in computer network security management,avoid various losses and hazards that may occur after computer network attack,and ensure the smooth operation of computer network system,the article introduces machine learning algorithm to design and optimize.First of all,the research background is introduced,pointing out that the current computer network is mainly facing data leakage risk,DDoS attack risk,etc.On this basis,the computer learning algorithm is designed to optimize the computer network security management architecture,comb the key technical means,and finally runs the test with the help of the simulation platform.The research results prove that the computer network security management technology based on machine learning works well,and can more accurately identify the potential risks and ensure the security of the computer network.
作者
孙铖
SUN Cheng(Renmin University of China,Beijing 100080,China)
出处
《移动信息》
2023年第1期160-162,共3页
MOBILE INFORMATION
关键词
机器学习
计算机网络
安全管理
Machine learning
Computer network
Security management
