Tatsuya Chuman

Rei Aso, Tatsuya Chuman, Hitoshi Kiya

In this paper, a privacy preserving image classification method is proposed under the use of ConvMixer models. To protect the visual information of test images, a test image is divided into blocks, and then every block is encrypted by using a random orthogonal matrix. Moreover, a ConvMixer model trained with plain images is transformed by the random orthogonal matrix used for encrypting test images, on the basis of the embedding structure of ConvMixer. The proposed method allows us not only to use the same classification accuracy as that of ConvMixer models without considering privacy protection but to also enhance robustness against various attacks compared to conventional privacy-preserving learning.

Tatsuya Chuman, Yousuke Udagawa, Hitoshi Kiya

A privacy-preserving clothing classification scheme is presented to enable secure occupant-centric control (OCC) systems. Although the utilization of camera images for HVAC control has been widely studied to optimize thermal comfort, privacy protection of occupant images has not been considered in prior works. While various privacy-preserving methods have been proposed for image classification, applying conventional schemes results in severe accuracy degradation. In this paper, we introduce a privacy-preserving classification method using Vision Transformer (ViT) applied to clothing insulation estimation. In an experiment using the DeepFashion dataset categorized by clothing insulation, while the conventional pixel-based method suffers a severe accuracy drop, our scheme maintains a high accuracy on encrypted images, showing no degradation from plain images across all categories.

Tatsuya Chuman, Hitoshi Kiya

The aim of this paper is to evaluate the security of a block-based image encryption for the vision transformer against jigsaw puzzle solver attacks. The vision transformer, a model for image classification based on the transformer architecture, is carried out by dividing an image into a grid of square patches. Some encryption schemes for the vision transformer have been proposed by applying block-based image encryption such as block scrambling and rotating to patches of the image. On the other hand, the security of encryption scheme for the vision transformer has never evaluated. In this paper, jigsaw puzzle solver attacks are utilized to evaluate the security of encrypted images by regarding the divided patches as pieces of a jigsaw puzzle. In experiments, an image is resized and divided into patches to apply block scrambling-based image encryption, and then the security of encrypted images for the vision transformer against jigsaw puzzle solver attacks is evaluated.

Tatsuya Chuman, Hitoshi Kiya

In this paper, we propose a novel learnable image encryption method for privacy-preserving deep neural networks (DNNs). The proposed method is carried out on the basis of block scrambling used in combination with data augmentation techniques such as random cropping, horizontal flip and grid mask. The use of block scrambling enhances robustness against various attacks, and in contrast, the combination with data augmentation enables us to maintain a high classification accuracy even when using encrypted images. In an image classification experiment, the proposed method is demonstrated to be effective in privacy-preserving DNNs.

Warit Sirichotedumrong, Tatsuya Chuman, Hitoshi Kiya

A new grayscale-based block scrambling image encryption scheme is presented to enhance the security of Encryption-then-Compression (EtC) systems, which are used to securely transmit images through an untrusted channel provider. The proposed scheme enables the use of a smaller block size and a larger number of blocks than the conventional scheme. Images encrypted using the proposed scheme include less color information due to the use of grayscale images even when the original image has three color channels. These features enhance security against various attacks, such as jigsaw puzzle solver and brute-force attacks. Moreover, it allows the use of color sub-sampling, which can improve the compression performance, although the encrypted images have no color information. In an experiment, encrypted images were uploaded to and then downloaded from Facebook and Twitter, and the results demonstrated that the proposed scheme is effective for EtC systems, while maintaining a high compression performance.

Tatsuya Chuman, Warit Sirichotedumrong, Hitoshi Kiya

A block scrambling-based encryption scheme is presented to enhance the security of Encryption-then-Compression (EtC) systems with JPEG compression, which allow us to securely transmit images through an untrusted channel provider, such as social network service providers. The proposed scheme enables the use of a smaller block size and a larger number of blocks than the conventional scheme. Images encrypted using the proposed scheme include less color information due to the use of grayscale images even when the original image has three color channels. These features enhance security against various attacks such as jigsaw puzzle solver and brute-force attacks. In an experiment, the security against jigsaw puzzle solver attacks is evaluated. Encrypted images were uploaded to and then downloaded from Facebook and Twitter, and the results demonstrated that the proposed scheme is effective for EtC systems.

Warit Sirichotedumrong, Tatsuya Chuman, Hitoshi Kiya

This paper considers a new grayscale-based image encryption for Encryption-then-Compression (EtC) systems with JPEG compression. Firstly, generation methods of grayscale-based images are discussed in terms of the selection of color space. In addition, a new JPEG quantization table for the grayscale-based images is proposed to provide a better compression performance. Moreover, the quality of both images uploaded to Social Network Services (SNS) and downloaded from SNS, are discussed and evaluated. In the experiments, encrypted images are compressed using various compression parameters and quantization tables, and uploaded to Twitter and Facebook. The results proved that the selection of color space and the proposed quantization table can improve the compression performances of not only uploaded images but also downloaded ones.

Tatsuya Chuman, Kenta Iida, Warit Sirichotedumrong et al.

Encryption-then-Compression (EtC) systems have been proposed to securely transmit images through an untrusted channel provider. In this study, EtC systems were applied to social media like Twitter that carry out image manipulations. The block scrambling-based encryption schemes used in EtC systems were evaluated in terms of their robustness against image manipulation on social media. The aim was to investigate how five social networking service (SNS) providers, Facebook, Twitter, Google+, Tumblr and Flickr, manipulate images and to determine whether the encrypted images uploaded to SNS providers can avoid being distorted by such manipulations. In an experiment, encrypted and non-encrypted JPEG images were uploaded to various SNS providers. The results show that EtC systems are applicable to the five SNS providers.

Tatsuya Chuman, Hitoshi Kiya

Encryption-then-Compression (EtC) systems have been considered for the user-controllable privacy protection of social media like Twitter. The aim of this paper is to evaluate the security of block scrambling-based encryption schemes, which have been proposed to construct EtC systems. Even though this scheme has enough key spaces against brute-force attacks, each block in encrypted images has almost the same correlation as that of original images. Therefore, it is required to consider the security from different viewpoints from number theory-based encryption methods with provable security such as RSA and AES. In this paper, we evaluate the security of encrypted images including JPEG distortion by using automatic jigsaw puzzle solvers.

Warit Sirichotedumrong, Tatsuya Chuman, Shoko Imaizumi et al.

This paper proposes a new block scrambling encryption scheme that enhances the security of encryption-then-compression (EtC) systems for JPEG images, which are used, for example, to securely transmit images through an untrusted channel provider. The proposed method allows the use of a smaller block size and a larger number of blocks than the conventional ones. Moreover, images encrypted using proposed scheme include less color information due to the use of grayscale even when the original image has three color channels. These features enhance security against various attacks such as jigsaw puzzle solver and brute-force attacks. The results of an experiment in which encrypted images were uploaded to and then downloaded from Twitter and Facebook demonstrated the effectiveness of the proposed scheme for EtC systems.