HondaRUM
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System that aims to detect and mitigate DDoS attacks using Machine Learning techniques & SDN.
Programmed the SDN controller to monitor the traffic, predict the traffic behaviour and detect DDOS traffic in the cloud network and mitigate it. Machine learning SVM algorithm was used to predict …
DDoS attacks detection based on SVM and mitigation in a Software-Defined Network.
This project aims to detect Distributed Denial of Service (DDoS) attacks within a Software-Defined Network (SDN) using an SVM framework for classifying network traffic as normal or anomalous
Applying Machine Learning model (SVM) into DDoS attack detection in SDN.
Python based DDoS attack detection and mitigation system built over Ryu controllers and Mininet SDN,
SDN-DDoS-Monitor: A simple machine learning tool for detecting botnet attacks
sdn network ddos detection using machine learning
DDoS attacks detection by using SVM on SDN networks.
温州大学《机器学习》课程资料（代码、课件等）
I am trying to propose a cache system for p4 data plane.
An attempt at verifying Zipf's law for programming languages
Hypothesis testing of Zipf's Law for natural languages (NLP SP19)
To perform load balancing on fat tree topology using SDN Controller i.e. Floodlight and OpenDaylight.
基于Ryu的SDN中小型网络搭建
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 …
