论文标题
图像和模型转换带有视觉变压器的秘密钥匙
Image and Model Transformation with Secret Key for Vision Transformer
论文作者
论文摘要
在本文中，我们提出了转换图像和视觉变压器（VIT）模型的联合使用，该模型使用秘密钥匙进行了转换。我们首次展示了经过普通图像训练的模型可以直接转换为基于VIT体系结构训练的模型，并且在使用使用密钥加密的测试图像时，转换模型的性能与经过纯图像训练的模型相同。此外，提出的方案不需要任何特殊准备的数据进行培训模型或网络修改，因此它还使我们可以轻松更新秘密密钥。在实验中，在CIFAR-10数据集中的图像分类任务中，根据性能降解和模型保护性能评估了提出方案的有效性。
In this paper, we propose a combined use of transformed images and vision transformer (ViT) models transformed with a secret key. We show for the first time that models trained with plain images can be directly transformed to models trained with encrypted images on the basis of the ViT architecture, and the performance of the transformed models is the same as models trained with plain images when using test images encrypted with the key. In addition, the proposed scheme does not require any specially prepared data for training models or network modification, so it also allows us to easily update the secret key. In an experiment, the effectiveness of the proposed scheme is evaluated in terms of performance degradation and model protection performance in an image classification task on the CIFAR-10 dataset.
