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
—