My University of Milan thesis work about Data-efficient GANs for malware behavior-based image generation
DC-GAN Algoritm is generating malicious samples. A comparison between GAN-generated and SMOTE-generated has been added. The malware classifier is evaluating before the usage of generated samples, and after the generation of samples from the GAN. Performances are low, but it needs to be trained and optimised a little bit more.