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An image steganography scheme based on ResNet

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Abstract

In recent years, deep learning has been used in steganography scheme, and the implemented solution had a large hidden capacity. In order to further study the effect of basic deep learning network on image steganography, a deep learning image steganography scheme based on ResNet was proposed in this paper, which applied the idea of residual blocks in ResNet to the field of image steganography. Image hiding and image extraction were realized by encoder network and decoder network. In the proposed scheme, by setting the balance parameter during training, different hiding and extraction qualities could be obtained for different scenarios. At the same time, a new performance analysis method was proposed for the field of deep steganography: the scatter plots of PSNR and SSIM. For a test set with a large amount of data, it could clearly reflect the performance of the solution, and it had a certain degree of application value in the field of deep steganography. The experimental results showed that the scheme had better invisibility when hiding, high data accuracy when extracting, and had certain advantages compared with the existing scheme. And it performed better when detected by steganalysis tools.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (No. 61976126), Shandong Natural Science Foundation (No. ZR2019MF003).

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Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, 266+590, Qingdao, China

    Lianshan Liu, Lingzhuang Meng & Yanjun Peng

  2. Office of Network Security and Informatization, Shandong University of Science and Technology, 266+590, Qingdao, China

    **aoli Wang

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  1. Lianshan Liu
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  2. Lingzhuang Meng
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  4. Yanjun Peng
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Correspondence to Lianshan Liu.

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Liu, L., Meng, L., Wang, X. et al. An image steganography scheme based on ResNet. Multimed Tools Appl 81, 39803–39820 (2022). https://doi.org/10.1007/s11042-022-13206-2

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