Adversarial Lab

This project is a Web-based Tool for visualisation and generation of adversarial examples by attacking ImageNet Models like VGG, AlexNet, ResNet etc.

Visualizing and Comparision of Various Adversarial Attacks on user uploaded images using a simple interface, using the DNN framework Pytorch, using popular SOTA Pretrained TorchVision ModelZoo. The Following Attacks have been implemented so far:

1. FGSM

   • Fast Gradient Sign Method, Untargeted
   • Fast Gradient Sign Method, Targeted

2. Iterative

   • Basic Iterative Method, Untargeted
   • Least Likely Class Iterative Method

3. DeepFool, untargeted

4. LBFGS, targeted

Coming Soon: Carlini-Wagner l2, and Many More