基于人工智能的DDoS攻击检测方法研究进展  

The Survey of DDoS Detection Methods Based on Artificial Intelligence

作　　者：康重 赵恭震 Kang Zhong;Zhao Gongzhen(University Of International Relations,Beijing 100091,China)

机构地区：[1]国际关系学院,北京100091

出　　处：《信息通信技术》2021年第6期61-65,84,共6页Information and communications Technologies

摘　　要：随着互联网广泛应用,DDoS攻击已经成为影响网络设施安全的主要因素之一,给网络造成了严峻的安全威胁。文章首先介绍DDoS攻击原理和不同的攻击类型,分析基于人工智能的DDoS攻击检测三种算法:基于分类算法、基于聚类算法和基于深度学习算法检测。在此基础上,文章分别总结每种检测方法的研究和分析现状,给出每种检测方法的实际应用场景,最后说明三种检测方法的优缺点,给研究人员提供了参考和选择。With the rapid development of the Internet, DDoS attacks have become one of the main factors affecting the security of network facilities, posing severe security threats to enterprises and society. This article first introduces the principles of DDoS attacks and different types of attacks, and then summarizes DDoS attack detection methods based on artificial intelligence,which are mainly divided into three categories: detection based on classification algorithms, detection based on clustering algorithms, and detection based on deep learning algorithms. On this basis, the research and analysis status of each type of detection method is summarized correspondingly, and the actual application scenarios of each type of detection methods are explained. Finally, the characteristics, advantages and disadvantages of the three detection methods are discussed, which provide references and choices for subsequent researchers.

关 键 词：DDOS攻击 人工智能 机器学习 深度学习 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]