Adversarial watermark: A robust and reliable watermark against removal

Abstract

Digital image watermarking used to be an important tool for copyright protection. However, as neural network-based watermark removal methods have been proposed in recent years, the embedded watermark is increasingly easy to be erased, which poses a great threat to copyright protection. To address this issue, we propose an adversarial visible watermark scheme, which combines the visible watermark with the adversarial perturbation. By attacking the watermark removal network, we maximize the resistance of visible watermark against removal while minimizing the visual distortion. To further improve the robustness against various transformations (e.g. cropping, JPEG compression), we employ the region of interest and random pre-processing to embed the adversarial visible watermark. The experimental results show that the proposed scheme can effectively resist the removal of watermarks on different datasets and network structures while having good transferability and robustness, which enables the watermark to continue to be an effective copyright protection method.