论文标题
零日DDOS攻击检测
Zero-day DDoS Attack Detection
论文作者
论文摘要
检测零日（新颖）攻击的能力在网络安全行业中变得至关重要。由于不断发展的攻击签名，现有的网络入侵检测系统通常无法检测到这些威胁。该项目旨在通过利用进入私人网络之前捕获的网络流量来解决检测零日DDO（分布式拒绝服务）攻击的任务。现代特征提取技术与神经网络结合使用，以确定网络数据包是良性还是恶意。
The ability to detect zero-day (novel) attacks has become essential in the network security industry. Due to ever evolving attack signatures, existing network intrusion detection systems often fail to detect these threats. This project aims to solve the task of detecting zero-day DDoS (distributed denial-of-service) attacks by utilizing network traffic that is captured before entering a private network. Modern feature extraction techniques are used in conjunction with neural networks to determine if a network packet is either benign or malicious.
