Publication detail

Towards Evaluating Quality of Datasets for Network Traffic Domain

ČEJKA, T. HYNEK, K. SOUKUP, D. TISOVČÍK, P.

Original Title

Towards Evaluating Quality of Datasets for Network Traffic Domain

Type

conference paper

Language

English

Original Abstract

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.

Keywords

Dataset; Data Quality; Network traffic analysis

Authors

ČEJKA, T.; HYNEK, K.; SOUKUP, D.; TISOVČÍK, P.

Released

20. 12. 2021

Publisher

Institute of Electrical and Electronics Engineers

Location

Izmir

ISBN

978-3-903176-36-2

Book

Proceedings of the 17th International Conference on Network Service Management (CNSM 2021)

Pages from

264

Pages to

268

Pages count

5

URL

BibTex

@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"
}