2017
SafetyNet: Detecting and Rejecting Adversarial Examples Robustly
ICCV 2017poster
We describe a method to produce a network where current methods such as DeepFool have great difficulty producing adversarial samples. Our construction suggests some insights into how deep networks work. We provide a reasonable analyses that our construction is difficult to defeat, and show experimen…