Revisiting Gradient Boosting-Based Approaches for Learning Imbalanced Data: A Case of Anomaly Detection on Power Grids

Revisiting Gradient Boosting-Based Approaches for Learning Imbalanced Data: A Case of Anomaly Detection on Power Grids

Gradient boosting ensembles have been used in the cyber-security area for many years; nonetheless, their efficacy and accuracy for intrusion detection systems (IDSs) remain questionable, particularly when dealing with problems involving imbalanced data. This article fills the void in the existing bo...

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Bibliographic Details
Main Authors: Maya Hilda Lestari Louk, Bayu Adhi Tama
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Big Data and Cognitive Computing
Subjects:
imbalance learning
oversampling
anomaly detection
gradient boosting ensembles
power grid
MWMOTE
Online Access:https://www.mdpi.com/2504-2289/6/2/41

Internet

https://www.mdpi.com/2504-2289/6/2/41

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