SYSTEM AND METHOD OF MEASURING THE ROBUSTNESS OF A DEEP NEURAL NETWORK

A method of evaluating the robustness of a Deep Neural Network (DNN) model. The method includes obtaining a set of training data-points correctly predicted by the DNN model and obtaining a set of realistic transformations of the set of training data-points correctly predicted by the DNN model, where the set of realistic transformations corresponding to additional data-points within a predetermined mathematical distance from each of a training data-point of the set of training data-points. The method also includes creating a robustness profile corresponding to whether the DNN model accurately predicts an outcome for the additional data-points of the set of realistic transformations and generating a robustness evaluation of the DNN model based on the robustness profile.