1 citations · 1 across the 7 of their papers we have counts for
7 papers
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…
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…
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…
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…
A universal detector of CNN-generated images using properties of checkerboard artifacts in the frequency domain
Miki Tanaka, Sayaka Shiota, Hitoshi Kiya
We propose a novel universal detector for detecting images generated by using CNNs. In this paper, properties of checkerboard artifacts in CNN-generated images are considered, and…
Fake-image detection with Robust Hashing
Miki Tanaka, Hitoshi Kiya
In this paper, we investigate whether robust hashing has a possibility to robustly detect fake-images even when multiple manipulation techniques such as JPEG compression are applie…
CycleGAN without checkerboard artifacts for counter-forensics of fake-image detection
Takayuki Osakabe, Miki Tanaka, Yuma Kinoshita +1
In this paper, we propose a novel CycleGAN without checkerboard artifacts for counter-forensics of fake-image detection. Recent rapid advances in image manipulation tools and deep…