A Larger Capacity Data Hiding Scheme Based on DNN

• Main Authors: Liu, L. (Author), Meng, L. (Author), Peng, Y. (Author), Wang, X. (Author), Zheng, W. (Author)
• Format: Article
• Language: English
• Published: Hindawi Limited 2022
• Subjects: Capacity data; Carrier images; Color; Colour image; Data extraction; Data hiding technologies; Data mining; Data-hiding; Deep neural networks; Image processing; Network-based; Secret images; Steganography; Visual differences; Visual effects
• Online Access: View Fulltext in Publisher

 With the in-depth research in data hiding technology, the latest data hiding schemes using deep neural network (DNN) could hide the full-size color image into the same size color image. This paper proposed a larger capacity data hiding scheme based on DNN, which could hide large-size color image into small-size color image. This scheme used DNN in both the data hiding stage and data extraction stage. And the two networks were obtained through adversarial training and used in pairs. The information ratio between the carrier image and the secret image had reached 1: 4. The image obtained after hiding the data did not change much compared with the carrier image, and the extracted image had the same size and no visual difference compared with the secret image. It could be seen from the simulation experiment that, compared with the existing DNN-based data hiding scheme, even if the capacity of the proposed scheme was 4 times larger than that of the existing scheme, the visual effect and PSNR were also better than some existing schemes. © 2022 Lianshan Liu et al.