Description
In the space of adversarial perturbation against classifier accuracy, the ARA is the area between a classifier's curve and the straight line defined by a naive classifier's maximum accuracy. Intuitively, the ARA measures a combination of the classifier’s predictive power and its ability to overcome an adversary. Importantly, when contrasted against existing robustness metrics, the ARA takes into account the classifier’s performance against all adversarial examples, without bounding them by some arbitrary .
Papers Using This Method
Adversarial multi-task underwater acoustic target recognition: towards robustness against various influential factors2024-11-05Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness2019-06-07Fake News Detection via NLP is Vulnerable to Adversarial Attacks2019-01-05