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 l...Show MoreMetadata
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.
Date of Conference: 25-29 October 2021
Date Added to IEEE Xplore: 02 December 2021
ISBN Information: