71 citations · 304 across the 98 of their papers we have counts for
102 papers
Block-Wise Encryption for Reliable Vision Transformer models
Hitoshi Kiya, Ryota Iijima, Teru Nagamori
This article presents block-wise image encryption for the vision transformer and its applications. Perceptual image encryption for deep learning enables us not only to protect the…
Security Evaluation of Compressible and Learnable Image Encryption Against Jigsaw Puzzle Solver Attacks
Tatsuya Chuman, Nobutaka Ono, Hitoshi Kiya
Several learnable image encryption schemes have been developed for privacy-preserving image classification. This paper focuses on the security block-based image encryption methods…
Enhanced Security with Encrypted Vision Transformer in Federated Learning
Rei Aso, Sayaka Shiota, Hitoshi Kiya
Federated learning is a learning method for training models over multiple participants without directly sharing their raw data, and it has been expected to be a privacy protection…
Enhanced Security against Adversarial Examples Using a Random Ensemble of Encrypted Vision Transformer Models
Ryota Iijima, Miki Tanaka, Sayaka Shiota +1
Deep neural networks (DNNs) are well known to be vulnerable to adversarial examples (AEs). In addition, AEs have adversarial transferability, which means AEs generated for a source…
Generative Model-Based Attack on Learnable Image Encryption for Privacy-Preserving Deep Learning
AprilPyone MaungMaung, Hitoshi Kiya
In this paper, we propose a novel generative model-based attack on learnable image encryption methods proposed for privacy-preserving deep learning. Various learnable encryption me…
Combined Use of Federated Learning and Image Encryption for Privacy-Preserving Image Classification with Vision Transformer
Teru Nagamori, Hitoshi Kiya
In recent years, privacy-preserving methods for deep learning have become an urgent problem. Accordingly, we propose the combined use of federated learning (FL) and encrypted image…
A Privacy Preserving Method with a Random Orthogonal Matrix for ConvMixer Models
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 div…
Color-NeuraCrypt: Privacy-Preserving Color-Image Classification Using Extended Random Neural Networks
Zheng Qi, AprilPyone MaungMaung, Hitoshi Kiya
In recent years, with the development of cloud computing platforms, privacy-preserving methods for deep learning have become an urgent problem. NeuraCrypt is a private random neura…
A Jigsaw Puzzle Solver-based Attack on Block-wise Image Encryption for Privacy-preserving DNNs
Tatsuya Chuman, Hitoshi Kiya
Privacy-preserving deep neural networks (DNNs) have been proposed for protecting data privacy in the cloud server. Although several encryption schemes for visually protection have…
Access Control with Encrypted Feature Maps for Object Detection Models
Teru Nagamori, Hiroki Ito, AprilPyone MaungMaung +1
In this paper, we propose an access control method with a secret key for object detection models for the first time so that unauthorized users without a secret key cannot benefit f…
On the Adversarial Transferability of ConvMixer Models
Ryota Iijima, Miki Tanaka, Isao Echizen +1
Deep neural networks (DNNs) are well known to be vulnerable to adversarial examples (AEs). In addition, AEs have adversarial transferability, which means AEs generated for a source…
StyleGAN Encoder-Based Attack for Block Scrambled Face Images
AprilPyone MaungMaung, Hitoshi Kiya
In this paper, we propose an attack method to block scrambled face images, particularly Encryption-then-Compression (EtC) applied images by utilizing the existing powerful StyleGAN…
On the Transferability of Adversarial Examples between Encrypted Models
Miki Tanaka, Isao Echizen, Hitoshi Kiya
Deep neural networks (DNNs) are well known to be vulnerable to adversarial examples (AEs). In addition, AEs have adversarial transferability, namely, AEs generated for a source mod…
An Access Control Method with Secret Key for Semantic Segmentation Models
Teru Nagamori, Ryota Iijima, Hitoshi Kiya
A novel method for access control with a secret key is proposed to protect models from unauthorized access in this paper. We focus on semantic segmentation models with the vision t…
A Detection Method of Temporally Operated Videos Using Robust Hashing
Shoko Niwa, Miki Tanaka, Hitoshi Kiya
SNS providers are known to carry out the recompression and resizing of uploaded videos/images, but most conventional methods for detecting tampered videos/images are not robust eno…
Privacy-Preserving Image Classification Using ConvMixer with Adaptive Permutation Matrix
Zheng Qi, AprilPyone MaungMaung, Hitoshi Kiya
In this paper, we propose a privacy-preserving image classification method using encrypted images under the use of the ConvMixer structure. Block-wise scrambled images, which are r…
Template matching with white balance adjustment under multiple illuminants
Teruaki Akazawa, Yuma Kinoshita, Hitoshi Kiya
In this paper, we propose a novel template matching method with a white balancing adjustment, called N-white balancing, which was proposed for multi-illuminant scenes. To reduce th…
An Encryption Method of ConvMixer Models without Performance Degradation
Ryota Iijima, Hitoshi Kiya
In this paper, we propose an encryption method for ConvMixer models with a secret key. Encryption methods for DNN models have been studied to achieve adversarial defense, model pro…
Image and Model Transformation with Secret Key for Vision Transformer
Hitoshi Kiya, Ryota Iijima, MaungMaung Aprilpyone +1
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 wit…
Security Evaluation of Compressible Image Encryption for Privacy-Preserving Image Classification against Ciphertext-only Attacks
Tatsuya Chuman, Hitoshi Kiya
The security of learnable image encryption schemes for image classification using deep neural networks against several attacks has been discussed. On the other hand, block scrambli…
Access Control of Semantic Segmentation Models Using Encrypted Feature Maps
Hiroki Ito, AprilPyone MaungMaung, Sayaka Shiota +1
In this paper, we propose an access control method with a secret key for semantic segmentation models for the first time so that unauthorized users without a secret key cannot bene…
Privacy-Preserving Image Classification Using Vision Transformer
Zheng Qi, AprilPyone MaungMaung, Yuma Kinoshita +1
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 meth…
Privacy-Preserving Image Classification Using Isotropic Network
AprilPyone MaungMaung, Hitoshi Kiya
In this paper, we propose a privacy-preserving image classification method that uses encrypted images and an isotropic network such as the vision transformer. The proposed method a…
Access Control of Object Detection Models Using Encrypted Feature Maps
Teru Nagamori, Hiroki Ito, April Pyone Maung Maung +1
In this paper, we propose an access control method for object detection models. The use of encrypted images or encrypted feature maps has been demonstrated to be effective in acces…