  Neural networks are known to be vulnerable to adversarial examples. In this
note, we evaluate the two white-box defenses that appeared at CVPR 2018 and
find they are ineffective: when applying existing techniques, we can reduce the
accuracy of the defended models to 0%.

Computer Vision and Pattern Recognition;Cryptography and Security;Machine Learning;Machine Learning