adversarials_detection (in development)
repository contains detectors of adversarial examples
to generate attack (FGSM) was used foolbox 2.4.0 attack.py
adversarials_detection.ipynb demonstrates how to use adversarial detector
all experiments were performed using VGG architecture vgg.py
(to train model one could use cifar10training.py)
Detector algorithms are in detectors.py
Adversarial examples
Original image:
The same image with small perturbations:
Algorithms
Softmax output of NN for the pictures above:
As we see, "probability" of real class in perturbed image is still significant. It could be
used to teach binary classificator (0 - real, 1 - adversarial) with softmax as features.