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
Key words
cybersecurity/distributed denial of service/attack detection/deep learning
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