Destruction of Image Steganography using Generative Adversarial Networks

1 code implementation • 20 Dec 2019 • Isaac Corley, Jonathan Lwowski, Justin Hoffman

Digital image steganalysis, or the detection of image steganography, has been studied in depth for years and is driven by Advanced Persistent Threat (APT) groups', such as APT37 Reaper, utilization of steganographic techniques to transmit additional malware to perform further post-exploitation activity on a compromised host.

Blocking Generative Adversarial Network +3

DomainGAN: Generating Adversarial Examples to Attack Domain Generation Algorithm Classifiers

1 code implementation • 14 Nov 2019 • Isaac Corley, Jonathan Lwowski, Justin Hoffman

Our results conclude that GAN based DGAs are superior in evading DGA classifiers in comparison to traditional DGAs, and of the variants, the Wasserstein GAN with Gradient Penalty (WGANGP) is the highest performing DGA for uses both offensively and defensively.