A Survey on Data-Driven Learning for Intelligent Network Intrusion Detection Systems

A Survey on Data-Driven Learning for Intelligent Network Intrusion Detection Systems

An effective anomaly-based intelligent IDS (AN-Intel-IDS) must detect both known and unknown attacks. Hence, there is a need to train AN-Intel-IDS using dynamically generated, real-time data in an adversarial setting. Unfortunately, the public datasets available to train AN-Intel-IDS are ineluctably...

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Bibliographic Details
Main Authors: Ghada Abdelmoumin, Jessica Whitaker, Danda B. Rawat, Abdul Rahman
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Electronics
Subjects:
imbalanced learning
adversarial learning
generative models
generative adversarial networks
oversampling
intrusion detection systems
Online Access:https://www.mdpi.com/2079-9292/11/2/213

Internet

https://www.mdpi.com/2079-9292/11/2/213

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