Self-Supervised Adversarial Example Detection by Disentangled Representation. (arXiv:2105.03689v4 [cs.CV] UPDATED)

Deep learning models are known to be vulnerable to adversarial examples that
are elaborately designed for malicious purposes and are imperceptible to the
human perceptual system. Autoencoder, when trained solely over benign examples,
has been widely used for (self-supervised) adversarial detection based on the
assumption that adversarial examples yield larger reconstruction errors.
However, because lacking adversarial examples in its training and the too
strong generalization ability of autoencoder, this assumption does not always
hold true in practice. To alleviate this …

arxiv detection example representation