"AdvImageNet-1K"

"1,000 images from the ImageNet validation set were selected as the dataset for adversarial attacks. These images cover a diverse set of categories and were uniformly preprocessed to match the input size and normalization required by the models. This subset was used to generate and evaluate adversarial examples, testing the models\u2019 classification robustness under perturbed inputs while also assessing their performance on standard images. By selecting high-quality images with accurate labels, the experiments can effectively evaluate the effectiveness of adversarial attack methods using a limited sample."