ashwinn-v/Traffic-classifier-SDN
A system that could classify DNS, Telnet, Ping, Voice, Game, and Video traffic flows based on packet and byte information simulated by the Distributed Internet Traffic Generator (D-ITG) tool in an Software Defined Network (SDN) based network topology with Open vSwitch (OVS) using machine learning algorithms such as Logistic regression,K-Means clustering,K nearest neighbours, SVC, Gaussian NB and Random Forest Classifier.
This system helps network administrators and engineers classify different types of network traffic, such as DNS, Telnet, Ping, Voice, Game, and Video flows. By analyzing packet and byte information from a simulated network, it identifies and categorizes traffic using various machine learning techniques. Network operations professionals managing Software-Defined Networks (SDNs) can use this to understand network usage.
No commits in the last 6 months.
Use this if you need to automatically identify and categorize different traffic types within a simulated Software-Defined Network environment to better manage network resources.
Not ideal if you need to classify traffic in a live, production network environment or require integration with proprietary network hardware.
Stars
44
Forks
7
Language
Python
License
—
Category
Last pushed
Dec 22, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/ashwinn-v/Traffic-classifier-SDN"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GACWR/OpenUBA
A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for...
nfstream/nfstream
NFStream: a Flexible Network Data Analysis Framework.
echowei/DeepTraffic
Deep Learning models for network traffic classification
faucetsdn/poseidon
Poseidon is a python-based application that leverages software defined networks (SDN) to acquire...
CESNET/cesnet-datazoo
CESNET DataZoo: A toolset for large network traffic datasets