基于大数据的网络安全态势感知技术探讨
Exploration of network security situation awareness technology based on big data
谌颃 1张袖斌 1肖斌1
作者信息
- 1. 广州科技贸易职业学院,广东广州 511442
- 折叠
摘要
[目的/意义]随着大数据和云计算技术快速发展,网络海量化数据安全、网络态势感知与预测已成为人们关注的重要问题.[方法/过程]从网络数据访问和传输的安全态势感知着手,提出依托卷积神经网络(Convolutional Neural Networks,CNN)、DS证据理论的网络安全态势感知算法,对网络链路或节点面临的网络攻击、网络漏洞等做出融合识别分析,客观地反映在某一时段内网络全局的攻击分布情况.[结果/结论]可准确地感知监测计算机主机和网络服务的安全态势情况,准确率为80%以上,能够为网络攻击识别和追溯提供支持.
Abstract
[Purpose/Significance]With the rapid development of cloud computing technology,more and more enterprises and individuals are storing data in cloud environments.The secure transmission of data in the cloud environment has become an urgent problem to be solved.[Method/Process]Starting from the security situation awareness of network data access and transmission,a network security situation awareness algorithm based on CNN(Convolutional Neural Networks)convolutional neural network and DS evidence theory is proposed to comprehensively identify and analyze network attacks and vulnerabilities faced by network links or nodes,objectively reflecting the global attack distribution of the network during a certain period of time..[Results/Conclusion]The network situational awareness and evaluation scheme based on CNN+D-S evidence theory can accurately perceive the security situation of monitoring computer hosts and network services,with a perception accuracy of over 80%,and can provide support for network attack identification and tracing.
关键词
大数据/网络安全/态势感知/云计算/网络攻击Key words
big data/network security/situational awareness/cloud computing/network attack引用本文复制引用
基金项目
2022年度广州市高等教育教学质量与教学改革工程名师工作室项目(2022MSGZS017)
2023年度普通高校重点科研平台和项目(2023CIPT012)
出版年
2024
NETL
NSTL
万方数据