NFStream: a Flexible Network Data Analysis Framework.

Deep Learning models for network traffic classification

Toolkit for processing PCAP file and transform into image of MNIST dataset

Pytorch implementation of deep packet: a novel approach for encrypted traffic classification using deep learning

Efficient Network Traffic Classification via Pre-training Unidirectional Mamba

Privacy Preserving Collaborative Encrypted Network Traffic Classification (Differential Privacy, Federated Learning, Membership Inference Attack, Encrypted Traffic Classification)

Personal digital firewall ruleset for Surge on iOS and macOS, built for precise local traffic identification and policy control, with multilingual support for global deployment and flexible use.

一个流量分类的封装框架

CESNET DataZoo: A toolset for large network traffic datasets

Use deep learning to classify the malicious traffic, and use TensorFlow2.0 to carry out it.

tcbench is a Machine Learning and Deep Learning framework to train model from traffic packet time series or other input representations.

CESNET Models: Neural networks for network traffic classification

flowRecorder - a network traffic flow feature measurement tool

Using SIFT features, BOW, model: SVM

AutoML4ETC, a tool to automatically design efficient and high-performing neural architectures for encrypted traffic classification.

Jupyter notebooks with traffic classification examples using CESNET DataZoo and CESNET Models packages

In this paper, we proposed a deep learning model which achieves progress compared to LeNet-5 in the stability of Internet traffic classification.

A repository with models for encrypted traffic classification.

A web-based solution utilizing a robust tensorflow model for precise traffic condition classification made in ReactJs and FastAPI for backend.