cesnet-datazoo and cesnet-models

The models for network traffic classification provided by CESNET Models are designed to be used in conjunction with the large network traffic datasets and toolset offered by CESNET DataZoo.

cesnet-datazoo
56
Established
cesnet-models
56
Established
Maintenance 10/25
Adoption 8/25
Maturity 25/25
Community 13/25
Maintenance 10/25
Adoption 7/25
Maturity 25/25
Community 14/25
Stars: 44
Forks: 6
Downloads:
Commits (30d): 0
Language: Python
License: BSD-3-Clause
Stars: 22
Forks: 4
Downloads:
Commits (30d): 0
Language: Python
License: BSD-3-Clause
No risk flags
No risk flags

About cesnet-datazoo

CESNET/cesnet-datazoo

CESNET DataZoo: A toolset for large network traffic datasets

This tool provides a structured way to access and prepare large datasets of encrypted network traffic, specifically focusing on TLS and QUIC protocols. It helps network researchers and data scientists define training, validation, and test periods, select specific application classes, and apply data transformations. The output is ready-to-use dataframes for building and evaluating traffic classification models.

network-security-research traffic-classification encrypted-traffic dataset-preparation network-data-science

About cesnet-models

CESNET/cesnet-models

CESNET Models: Neural networks for network traffic classification

This project offers pre-trained neural networks to automatically identify and categorize different types of network traffic, even when encrypted. It takes raw network data or traffic flows as input and outputs classifications like 'video streaming,' 'gaming,' or 'file transfer.' Network administrators, security analysts, and researchers focused on network behavior would find this useful for monitoring and security.

network-security traffic-analysis network-monitoring intrusion-detection network-management

Related comparisons

Scores updated daily from GitHub, PyPI, and npm data. How scores work