Mal-AAEGAN: Adversarial Autoencoder with Double-Critic WGAN-GP for Malware Generation

Machine-learning ML malware detectors are known to be vulnerable to adversarial samples. Generative adversarial networks GANs such as MalGAN, Mal-LSGAN, and our previous Mal-D2GAN can craft adversarial malware to probe and harden these detectors, yet they operate directly on a high-dimensional,...