  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.
