WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches

WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches

The rise in cyber security issues has caused significant harm to tech world and thus society in recent years. Intrusion detection systems (IDSs) are crucial for the detection and the mitigation of the increasing risk of cyber attacks. False and disregarded alarms are a common problem for traditional...

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Bibliographic Details
Main Authors: Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Computers
Subjects:
deep learning (DL)
Wasserstein generative adversarial networks (WGANs)
random forest importance
intrusion detection system (IDS)
Online Access:https://www.mdpi.com/2073-431X/14/1/4
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