SDN Network DDOS Detection Using ML

Abstract

This paper describes a technique that uses the Ryu Controller and Mininet to identify and mitigate Distributed Denial of Service (DDoS) threats in Software Defined Networks (SDN). Using Mininet, the suggested method entails building a virtual network topology with connected switches and hosts. The Ryu Controller gathers traffic data while Mininet simulates several DDoS attack types, such as ICMP flood, land assault, TCP SYN flood, and UDP attacks. The Ryu Controller collects both benign and DDoS traffic into a dataset that is used to build a machine learning (ML) model that can detect DDoS attacks in real time.