大数据环境下的网络异常检测与分析技术研究  

Research on Network Anomaly Detection and Analysis Technology in Big Data Environment

作　　者：邓甜甜 DENG Tiantian(Changsha University Network and Modern Educational Technology Center,Changsha 410022,China)

机构地区：[1]长沙学院网络与现代教育技术中心,长沙410022

出　　处：《移动信息》2024年第8期181-183,共3页MOBILE INFORMATION

摘　　要：随着互联网的飞速发展和普及应用,网络安全问题日益突出。在大数据环境下,海量网络数据为异常行为检测与分析提供了新的机遇和挑战。文中围绕大数据环境下的网络异常检测与分析技术展开了研究,阐述了大数据和网络异常检测的概念及特点,分析了现有几种典型网络异常检测方法的优缺点,并在此基础上提出了一种改进的异常检测算法。With the rapid development and popularization of the Internet,network security issues have become increasingly prominent.In the big data environment,massive network data provides new opportunities and challenges for abnormal behavior detection and analysis.This paper focuses on the research of network anomaly detection and analysis technology in the big data environment,elaborates on the concepts and characteristics of big data and network anomaly detection,analyzes the advantages and disadvantages of several typical network anomaly detection methods,and proposes an improved anomaly detection algorithm based on this.

关 键 词：大数据 网络异常检测 机器学习 数据挖掘 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]