基于异构运维数据的数据中心网络安全检测方法分析  

Data Centre Network Security Detection Method Based on Heterogeneous Operation and Maintenance Data

作　　者：蔡雯 Cai Wen(State Administration of Radio and Television,Channel 623,Changzhou Jiangsu 213000,China)

机构地区：[1]国家广播电视总局623台,江苏常州213000

出　　处：《现代工业经济和信息化》2025年第3期91-93,共3页Modern Industrial Economy and Informationization

摘　　要：由于数据中心网络环境具有复杂性和动态性,在对其安全进行检测时,难以及时发现安全漏洞。为此,提出基于异构运维数据的数据中心网络安全检测方法。通过综合采集和预处理流程,将异构运维数据汇总并清洗。利用卷积神经网络,提取预处理后的数据特征,并构建特征知识库,以灵活应对网络安全的持续威胁。建立网络安全检测模型,通过实时监控和聚类分析,自动检测数据中心网络异常。实验结果表明,该方法能够高效地检测出数据中心网络环境中的漏洞,显著提升了网络安全检测的实时性。Due to the complexity and dynamics of the data centre network environment,it is difficult to detect security vulnerabilities in a timely manner.For this reason,a data centre network security detection method based on heterogeneous operation and maintenance data is proposed.Heterogeneous O&M data are aggregated and cleaned through an integrated collection and preprocessing process.Using convolutional neural networks,the pre-processed data features are extracted and a feature knowledge base is constructed to flexibly respond to continuous threats to network security.A network security detection model is established to automatically detect data centre network anomalies through real-time monitoring and cluster analysis.Experimental results show that the method can efficiently detect vulnerabilities in the data centre network environment and significantly improve the real-time network security detection.

关 键 词：异构运维数据 数据中心 网络安全检测 数据预处理 特征提取 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]