71 citations · 134 across the 52 of their papers we have counts for
4 papers · 1 filter
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…
Transfer Learning-Based Model Protection With Secret Key
MaungMaung AprilPyone, Hitoshi Kiya
We propose a novel method for protecting trained models with a secret key so that unauthorized users without the correct key cannot get the correct inference. By taking advantage o…
Training DNN Model with Secret Key for Model Protection
MaungMaung AprilPyone, Hitoshi Kiya
In this paper, we propose a model protection method by using block-wise pixel shuffling with a secret key as a preprocessing technique to input images for the first time. The prote…
Encryption Inspired Adversarial Defense for Visual Classification
MaungMaung AprilPyone, Hitoshi Kiya
Conventional adversarial defenses reduce classification accuracy whether or not a model is under attacks. Moreover, most of image processing based defenses are defeated due to the…