基于机器学习的DDoS攻击网络流量识别方法
DDoS attack network traffic identification based on machine learning
刘仲维1
作者信息
摘要
分布式拒绝服务(DDoS)攻击已然成为一种严重的网络安全威胁,文章介绍了DDoS攻击的概念、主要类型及其特征,概述了当前网络流量分析领域的研究现状,提出了构建流量统计特征、应用主成分分析进行流量降维的方法,采用了支持向量机和随机森林2 种算法识别与分类DDoS攻击流量.
Abstract
Distributed denial-of-service(DDoS)attacks have become a serious network security threat.This paper introduces the concept,main types and characteristics of DDoS attacks,summarizes the current research status in the field of network traffic analysis,proposes methods to construct traffic statistical features and apply principal component analysis for traffic dimensionality reduction,and uses support vector machine and random forest algorithms to identify and classify DDoS attack traffic.
关键词
DDoS攻击/机器学习/流量分析/模型识别Key words
DDoS attack/machine learning/traffic analysis/model identification引用本文复制引用
出版年
2024
NETL
NSTL
万方数据