A collection of datasets for network traffic classification and a set of tools to work with them.
The cesnet-datazoo package currently provides four datasets:
- CESNET-TLS22
- CESNET-QUIC22
- CESNET-TLS-Year22
- CESNET-QUICEXT-25
The core functions of the toolset are:
- A common API for downloading, configuring, and loading of four public datasets of encrypted network traffic.
- Extensive configuration options for:
- Selection of train, validation, and test periods.
- Selection of application classes and splitting classes between known and unknown.
- Data transformations, such as feature scaling.
- Built on suitable data structures for experiments with large datasets. There are several caching mechanisms to make repeated runs faster, for example, when searching for the best model configuration.
- Datasets are offered in multiple sizes to give users an option to start the experiments at a smaller scale (also faster dataset download, disk space, etc.). The default is the S size containing 25 million samples.
See a related project CESNET Models providing pretrained neural networks for traffic classification.