Fast Locally Optimal Detection of Targeted Universal Adversarial Perturbations
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2022.3169922
Abstract: This paper proposes a locally-optimal generalized likelihood ratio test (LO-GLRT) for detecting targeted attacks on a classifier, where the attacks add a norm-bounded targeted universal adversarial perturbation (UAP) to the classifier’s input. The paper includes… read more here.
Keywords: glrt; universal adversarial; locally optimal; detection ... See more keywords