DEVICE AND METHOD FOR TRAINING A CLASSIFIER AND ASSESSING THE ROBUSTNESS OF A CLASSIFIER

Computer-implemented method for training a classifier (60), wherein the classifier (60) is configured to classify input signals of digital image data and/or audio data and training the classifier (60) is based on a perturbed input signal obtained by applying a perturbation provided from a plurality (ξ) of perturbations to an input signal provided from a training dataset, wherein the method comprises the following steps:* Providing a plurality of initial perturbations;* Adapting a perturbation from the plurality of initial perturbations to an input signal, wherein the input signal is randomly drawn from the training dataset and the perturbation is adapted to the input signal such that applying the perturbation to the input signal yields a second input signal, which is classified differently than the first input signal;* Providing a subset of the plurality of initial perturbations as plurality (ξ) of perturbations;Training the classifier (60) based on the plurality (ξ) of perturbations.