The goal of this project is to provide neural network architectures for traffic classification and their pre-trained weights.

The newest network architecture is named Multi-modal CESNET v2 (mm-CESNET-v2) and is visualized in the following picture. See the getting started page and models reference for more information.

🐸 🐸 See a related project CESNET DataZoo providing large TLS and QUIC traffic datasets. 🐸 🐸

📓 📓 Example Jupyter notebooks are included in a separate CESNET Traffic Classification Examples repo. 📓 📓

Multi-modal CESNET v2

Installation

Install the package from pip with:

pip install cesnet-models

or for editable install with:

pip install -e git+https://github.com/CESNET/cesnet-models

Papers

Models from the following papers are included:

• Fine-grained TLS services classification with reject option
  Jan Luxemburk and Tomáš Čejka
  Computer Networks, 2023

• Encrypted traffic classification: the QUIC case
  Jan Luxemburk and Karel Hynek
  2023 7th Network Traffic Measurement and Analysis Conference (TMA)