MalwareDetector.py detects malware by CNN on bytes, Adversarial_Malware_Generator.py generates an adversarial malware by appending some bytes at the end and perturbating them. Malware_DoNotExecute.exe is a malware to create adversarial example from.
Working around targeted and non-targeted Random noise attack, FGSM Explaining and Harnessing Adversarial Examples and PGD Towards Deep Learning Models Resistant to Adversarial Attacks and measuring their success rate against FGSM/PGD adversarial traning.
Jacobian-based Dataset Augmentation from Practical Black-Box Attacks against Machine Learning to approximate a surrogate model to use its gradients for atatck on target model which has obfuscated gradients defense machanism. Black-box attacks peforms better than white-box as already said in Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
A quick touch on Membership Inference Attacks Against Machine Learning Models, good inefrence rate was possible with only two shadow models on CIFAR10.
Poisoning Attacks based on Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks.