When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time

no code implementations • 18 Dec 2017 • David J. Miller, Yulia Wang, George Kesidis

Tested on MNIST and CIFAR-10 image databases under three prominent attack strategies, our approach outperforms previous detection methods, achieving strong ROC AUC detection accuracy on two attacks and better accuracy than recently reported for a variety of methods on the strongest (CW) attack.

Anomaly Detection General Classification