A production-ready SDN controller, and a highly-extensible SDN framework.

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.

Creates a simple Ryu app using the tutorials and then adds on to it.

TupleNet is a lightweight tool for building virtual-networking

SDN-DDoS-Monitor: A simple machine learning tool for detecting botnet attacks

Mininet SDN based experiments on load balancing and improving server response times

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

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

Use Mininet to create topologies with OpenFlow switches and install flows to simulate network operations

Network Stress-Test Automation Toolkit

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

Ryu controller application that redirects traffic following user's decisions

SDN controllers synchronization approach based on Reinforcement Learning aimed at reducing the average path cost (APC)

Uses POX to interact with the SDN controller

A Combination of Software Defined Network (SDN) And A Multi-Layer Perceptron (MLP) Neural Network That Results In The Mitigation of DDoS Attacks.

PCE developed on top of OpenDaylight for constraint based path calculation

implementation SDN based firewall on mininet using POX

Firewall in Software Defined Network (SDN)

Code for RnD project at IIT Bombay. This work was published at IEEE ICNP 2018 workshop P4EU.