Authors : A. Bindu; Ambati Venkata Sai Harika; Dandamudi Swetha; Malli Sahithi

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/59864mcv

Scribd : https://tinyurl.com/43zmd9ua

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY1031

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.

Keywords : Software-Defined Networking, DDoS , Ryu Controller, Mininet Simulation, Machine Learning , ICMP Flooding, Land Attack Simulation, TCP SYN Flooding, UDP Flooding, Network Security Enhancement, Anomaly Detection, Traffic Classification, Real-time Monitoring, Network Topology Emulation.

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