SDN networks (Software Defined Networking ) are exposed to new security threats and attacks, especially Distributed Denial of Service (DDoS) attacks. For this aim, we have proposed a model able to detect and mitigate attacks automatically in SDN networks using Machine Learning (ML)

DDoS attacks detection by using SVM on SDN networks.

An SDN application that gives its user the ability to control flows in an OpenFlow network without coding.

Applying Machine Learning model (SVM) into DDoS attack detection in SDN.

Service Function Chaining Application for Ryu SDN controller

This is my master's thesis project: "QoS implementation in Software Defined Network using Ryu Controller"

Dockerfiles and scripts to build Kathará Docker images.

This project is an implementation of Dijkstra Algorithm utilizing Ryu Controller and mininet for routing packets in network topologies.

Project holding the implementation and results of my thesis project at University of Trento, Italy

routing-implementation in SDN based on switch processing delay and remaining bandwidth

DDOS Mitigation System based on Ryu SDN Controller with Port Blocking Mechanism

Software Defined Network Monitor System

An SDN-based Network Slicing Platform of 5G Core Network

This project is created using Ryu controller which performs DIJKSTRA algorithm to find best paths, based on traffic flowing through links.

This is my study on detection and mitigation DDoS attacks in SDN

Intelligent SDN traffic classification using deep learning : Generating and classifying SDN network traffic to differentiate between normal and abnormal packets using deep learning.

This is an application for Ryu controller. It implements NSH (RFC8300) with SFC (RFC7665)

Implementation of a Software Defined Perimeter in Ryu SDN Framework

A Distributed and Software-Defined Firewall based on OpenFlow

VoIS-Net: An SDN-driven, Voice-assisted, Intent-based, Self-healing Network Framework