Machine Learning With Variational AutoEncoder for Imbalanced Datasets in Intrusion Detection

Machine Learning With Variational AutoEncoder for Imbalanced Datasets in Intrusion Detection

As a result of the explosion of security attacks and the complexity of modern networks, machine learning (ML) has recently become the favored approach for intrusion detection systems (IDS). However, the ML approach usually faces three challenges: massive attack variants, imbalanced data issues, and...

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Bibliographic Details
Main Authors: Ying-Dar Lin, Zi-Qiang Liu, Ren-Hung Hwang, Van-Linh Nguyen, Po-Ching Lin, Yuan-Cheng Lai
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Imbalanced dataset
machine learning
variational autoencoder
intrusion detection
Online Access:https://ieeexplore.ieee.org/document/9705580/

Internet

https://ieeexplore.ieee.org/document/9705580/

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