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.

翻译：检测零天(新奇)袭击的能力在网络安全行业中变得至关重要。由于袭击信号的不断演变,现有的网络入侵探测系统往往无法检测这些威胁。该项目旨在通过利用进入私人网络之前所捕捉的网络交通,解决探测零天DDoS(分布式拒绝服务)袭击的任务。现代特征提取技术与神经网络一起用来确定网络包是良性的还是恶意的。