01357nam a2200169 a 4500 20260901030334.0 250101s2019 xx o 000 0 eng d Zhuo Zhang Generative Reversible Data Hiding by Image to Image Translation via GANs arXiv 2019 text online resource The traditional reversible data hiding technique is based on cover image modification which inevitably leaves some traces of rewriting that can be more easily analyzed and attacked by the warder. Inspired by the cover synthesis steganography based generative adversarial networks, in this paper, a novel generative reversible data hiding scheme (GRDH) by image translation is proposed. First, an image generator is used to obtain a realistic image, which is used as an input to the image-to-image translation model with CycleGAN. After image translation, a stego image with different semantic information will be obtained. The secret message and the original input image can be recovered separately by a well-trained message extractor and the inverse transform of the image translation. Experimental results have verified the effectiveness of the scheme. Open access — freely available to read. https://arxiv.org/pdf/1905.02872v4 Read the full paper (PDF) ERES 650 650 0 0 0 3 CYB MAIN MAIN SCICOMP 2026-09-01 0 YGE000911 2026-09-01 03:03:34 https://arxiv.org/pdf/1905.02872v4 2026-09-01 PAPER