15 citations · 19 across the 5 of their papers we have counts for
5 papers · 1 filter
Square Attack: a query-efficient black-box adversarial attack via random search
Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion +1
We propose the Square Attack, a score-based black-box - and -adversarial attack that does not rely on local gradient information and thus is not affected by gradient…
Sparse and Imperceivable Adversarial Attacks
Francesco Croce, Matthias Hein
Neural networks have been proven to be vulnerable to a variety of adversarial attacks. From a safety perspective, highly sparse adversarial attacks are particularly dangerous. On t…
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack
Francesco Croce, Matthias Hein
The evaluation of robustness against adversarial manipulation of neural networks-based classifiers is mainly tested with empirical attacks as methods for the exact computation, eve…
Provable robustness against all adversarial -perturbations for
Francesco Croce, Matthias Hein
In recent years several adversarial attacks and defenses have been proposed. Often seemingly robust models turn out to be non-robust when more sophisticated attacks are used. One w…
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks
Francesco Croce, Jonas Rauber, Matthias Hein
Modern neural networks are highly non-robust against adversarial manipulation. A significant amount of work has been invested in techniques to compute lower bounds on robustness th…