Publication Details
Towards Evaluating Quality of Datasets for Network Traffic Domain
Dataset; Data Quality; Network traffic analysis
This paper deals with the quality of network traffic datasets created to train and validate machine learning classification and detection methods. Naturally, there is a long epoch of research targeted at data quality; however, it is focused mainly on data consistency, validity, precision, and other metrics, which are insufficient for network traffic use-cases. The rise of Machine learning usage in network monitoring applications requires a new methodology for evaluation datasets. There is a need to evaluate and compare traffic samples captured at different conditions and decide the usability of the already captured and annotated data. This paper aims to explain a use case of dataset creation, propose definitions regarding the quality of the network traffic datasets, and finally, describe a framework for datasets analysis.
@inproceedings{BUT182953,
author="Tomáš {Čejka} and Karel {Hynek} and Dominik {Soukup} and Peter {Tisovčík}",
title="Towards Evaluating Quality of Datasets for Network Traffic Domain",
booktitle="Proceedings of the 17th International Conference on Network Service Management (CNSM 2021)",
year="2021",
pages="264--268",
publisher="Institute of Electrical and Electronics Engineers",
address="Izmir",
doi="10.23919/CNSM52442.2021.9615601",
isbn="978-3-903176-36-2",
url="https://ieeexplore.ieee.org/abstract/document/9615601"
}