Detecting Amplification Attacks with Software Defined Networking

Abstract

Distributed denial of service (DDoS) is an attack that attempts to disrupt network service for various malicious purposes. It makes use of public services as reflectors to amplify the traffic, and thus called distributed reflection denial of service attacks. This type of attack forges source IP address, and makes it hard to filter the problematic packets. With Software Defined Networking (SDN) and machine learning techniques, we implement a system to detect DRDoS packets and block the amplification attacks automatically. DNS and NTP amplifications are two typical attacks of DDoS. By analyzing the traffic features, although our classifier is trained only for the DNS amplification attack, our system can identify and then block both DNS and NTP amplification attacks with great accuracy.