VAE-WACGAN: An Improved Data Augmentation Method Based on VAEGAN for Intrusion Detection
Wuxin Tian,
Yanping Shen,
Na Guo
et al.
Abstract:To address the class imbalance issue in network intrusion detection, which degrades performance of intrusion detection models, this paper proposes a novel generative model called VAE-WACGAN to generate minority class samples and balance the dataset. This model extends the Variational Autoencoder Generative Adversarial Network (VAEGAN) by integrating key features from the Auxiliary Classifier Generative Adversarial Network (ACGAN) and the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP… Show more
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