DDoS攻击的发展与检测技术研究  

A review of the development and detection technologies of DDoS attacks

作　　者：马立鑫 薛占双 刘海燕[1] Ma Lixin;Xue Zhanshuang;Liu Haiyan(School of Computer,North China Institute of Aerospace Engineering,Langfang 065000,China)

机构地区：[1]北华航天工业学院计算机学院,廊坊065000

出　　处：《现代计算机》2024年第20期52-56,62,共6页Modern Computer

基　　金：河北省教育厅项目(CXY2023013)。

摘　　要：在网络安全领域,分布式拒绝服务攻击(DDoS)因其对信息系统的严重威胁而备受关注。研究了DDoS攻击的演进历程,从20世纪90年代的洪水攻击到使用僵尸网络、物联网(IoT)设备和云服务的复杂攻击模式,展示了攻击方法和技术的多样化。还对DDoS攻击进行了详细的分类,包括基于攻击手段和流量的分类方法,以及基于流量分析、行为分析、机器学习和深度学习的检测技术,指出了这些技术的优点和局限性。此外,还介绍了当下较为成熟的DDoS检测工具与系统,如Suricata Snort,Bro(Zeek)以及防护服务Cloudflare,并讨论了DDoS攻击未来的发展趋势。In the field of network security,DDoS(Distributed Denial of Service)attacks are a major concern due to their severe threat to information systems.This study examines the evolution of DDoS attacks,from the flood attacks of the 1990s to the complex attack patterns utilizing botnets,Internet of Things(IoT)devices,and cloud services,highlighting the diversification of attack methods and techniques.It also provides a detailed classification of DDoS attacks,including methods based on attack vectors and traffic,as well as detection techniques based on traffic analysis,behavior analysis,machine learning,and deep learning,pointing out the advantages and limitations of these techniques.Furthermore,it introduces current mature DDoS detection tools and systems,such as Suricata,Snort,Bro(Zeek),and protection services like Cloudflare,and discusses future trends in DDoS attacks.

关 键 词：网络安全 分布式拒绝服务 攻击检测 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]