This article presents an overview of image transformation with a secret key and its
applications. Image transformation with a secret key enables us not only to protect visual …

Abstract Model inversion (MI) attacks aim to infer and reconstruct private training data by
abusing access to a model. MI attacks have raised concerns about the leaking of sensitive …

We propose a novel image transformation network for generating visually protected images
for privacy-preserving deep neural networks (DNNs). The proposed transformation network …

Privacy-preserving deep neural networks have become essential and have attracted the
attention of many researchers due to the need to maintain the privacy and the confidentiality …

The need for cloud servers for training deep neural network (DNN) models is increasing as
more complex architecture designs of DNN models are developed. Nevertheless, cloud …

In this paper, we propose a privacy-preserving image classification method that is based on
the combined use of encrypted images and the vision transformer (ViT). The proposed …

In this paper, we propose a privacy-preserving semantic segmentation method that uses
encrypted images and models with the vision transformer (ViT), called the segmentation …

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 …

The training of state-of-the-art deep learning models generally requires significant high-
quality data, including personal and sensitive data. To ensure privacy of the sensitive data …

In this paper, we propose a novel DNN watermarking method that utilizes a learnable image
transformation method with a secret key. The proposed method embeds a watermark pattern …