71 citations · 304 across the 98 of their papers we have counts for
5 papers · 2 filters
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…
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…