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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)
Implemented a network intrusion detection system for a software defined network using Random Forest method for classification of port and flow statistics.
This repository contains the assignments of course "ITCS 8166: Computer Comm & Networks". This course has been taken in Spring 2021 semester, as part of my PhD degree at UNC Charlotte.
This course is designed to train the hands-on capabilities for solving networking problems. In this course, you will learn basic network management tools and use them to solve practical problems.
MininetIDS is an integrated environment for developing and evaluating Machine Learning-based Intrusion Detection Systems in Software-Defined Networks. It combines Mininet for network emulation and Ryu for SDN control, enabling advanced IDS research and deployment.