ADVERSARIAL EXAMPLE DETECTION METHOD AND APPARATUS, COMPUTING DEVICE, AND NON-VOLATILE COMPUTER-READABLE STORAGE MEDIUM

An adversarial example detection method includes: acquiring training examples and training example labels corresponding thereto, wherein the training example labels comprises normal examples and adversarial examples; inputting the training examples into a target model to obtain a first predicted score vector of the training examples; adding a random perturbation at N times to the training examples to obtain N groups of comparative training examples; respectively inputting the N groups of comparative training examples into the target model to obtain a second predicted score vector of each group of comparative training examples; constructing feature data according to the first predicted score vector and the second predicted score vector of each group of comparative training examples; training a classification model according to the feature data and the training example labels corresponding to the feature to obtain a detector; and detecting input test data according to the detector.