| Authors |
C. Lee, H. Okada, T. Wada, C. Ben Naila, M. Katayama |
| Title |
A Study on Hidden Screen-Camera Communication Systems Using Adversarial Attack on CNN Depth Estimation Model |
| Authority |
The 5th World Symposium on Communication Engineering (WSCE 2022) |
| Summary |
Hidden screen-camera communication requires visual quality and robust communication performance.
In this study, we propose a hidden screen-camera communication system using an adversarial attack on a
convolutional neural network (CNN) depth estimation model. An adversarial attack on the CNN depth
estimation model can change the output of the CNN model while not being seen by a human vision system. We
take advantage of the adversarial attack to embed data into the output of the CNN depth estimation model to
achieve hidden screen-camera communication. For an initial study, we clarify the potential of the system by
evaluating performance while assuming that there are no noises and distortions by displays and cameras. |
| 年月 |
2022年9月 |
| DOI/Handle |
|
| 開催場所 |
Nagoya University, Japan / Online |
| 研究テーマ |
可視光通信／光無線通信
機械学習
|
| 言語 |
英語 |
| 原稿/プレゼン資料 |
 /  (ローカル限定) |
