Resampling imbalanced data for network intrusion detection datasets

Resampling imbalanced data for network intrusion detection datasets

Abstract Machine learning plays an increasingly significant role in the building of Network Intrusion Detection Systems. However, machine learning models trained with imbalanced cybersecurity data cannot recognize minority data, hence attacks, effectively. One way to address this issue is to use res...

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Bibliographic Details
Main Authors: Sikha Bagui, Kunqi Li
Format: Article
Language:English
Published: SpringerOpen 2021-01-01
Series:Journal of Big Data
Subjects:
Oversampling
Undersampling
Resampling
Imbalanced Data
Network Intrusion Detection Systems
SMOTE
Online Access:https://doi.org/10.1186/s40537-020-00390-x

Internet

https://doi.org/10.1186/s40537-020-00390-x

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