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About Machine Learning in Traffic Classification of SDN - Final Project Report
This document summarizes a student project that used machine learning models to classify network traffic flows in a software-defined networking (SDN) environment. The student implemented a virtual network using VirtualBox and Open vSwitch. Traffic was generated between hosts using D-ITG and classified using logistic regression (supervised) and K-means clustering (unsupervised). Logistic regression performed better at classifying DNS, Telnet, ping and voice traffic flows based on flow statistics collected by the Ryu SDN controller. The project provided a proof of concept for machine learning-based traffic classification but had limitations that could be addressed in future work.
Detailed Information
| Author: | ['faizan jutt'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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