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Towards Evaluating Quality of Datasets for Network Traffic Domain

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F21%3A10133379" target="_blank" >RIV/63839172:_____/21:10133379 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21240/21:00353111 RIV/00216305:26230/21:PU147764

  • Result on the web

    <a href="http://dx.doi.org/10.23919/CNSM52442.2021.9615601" target="_blank" >http://dx.doi.org/10.23919/CNSM52442.2021.9615601</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.23919/CNSM52442.2021.9615601" target="_blank" >10.23919/CNSM52442.2021.9615601</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards Evaluating Quality of Datasets for Network Traffic Domain

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    R - Projekt Ramcoveho programu EK

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 2021 17th International Conference on Network and Service Management

  • ISBN

    978-3-903176-36-2

  • ISSN

    2165-963X

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    264-268

  • Publisher name

    IEEE

  • Place of publication

    Piscataway , USA

  • Event location

    Izmir, Turecko

  • Event date

    Oct 25, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article