Fig. 5
From: A CE-GAN based approach to address data imbalance in network intrusion detection systems
CE-GAN consists of four key components: an encoder, decoder, generator, and discriminator. While the encoder-decoder pair handles dimensional transformation, the generator creates samples based on low-dimensional features, and the discriminator evaluates both sample authenticity and conditional constraints. The system is trained through multiple loss functions and incorporates modules such as normalization and classifier evaluation to achieve conditional generation.
