Universalization of any adversarial attack using very few test examples

18 May 2020Sandesh KamathAmit DeshpandeK V Subrahmanyam

Deep learning models are known to be vulnerable not only to input-dependent adversarial attacks but also to input-agnostic or universal adversarial attacks. Dezfooli et al. \cite{Dezfooli17,Dezfooli17anal} construct universal adversarial attack on a given model by looking at a large number of training data points and the geometry of the decision boundary near them... (read more)

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