LEXNet: A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification

This repository contains the Python implementation of LEXNet as described in the paper A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification.

Requirements

LEXNet has been implemented in Python 3 with the following packages:

• numpy
• opencv
• pandas
• pytorch with cuda
• pyyaml
• scikit-learn
• scipy

Usage

Run main.py with the following argument:

• configuration: name of the configuration file (string)

python main.py --config configuration/config.yml

Citation

@inproceedings{Fauvel23LEXNet,
  author = {Fauvel, K. and F. Chen and D. Rossi},
  title = {{A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification}},
  booktitle = {Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  year = {2023}
}