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Steganography with High Reconstruction Robustness: Hiding of Encrypted Secret Images

Author

Listed:
  • Xishun Zhu

    (School of Advanced Manufacturing, Nanchang University, Nanchang 330031, China)

  • Zhengliang Lai

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

  • Nanrun Zhou

    (School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China)

  • Jianhua Wu

    (School of Information Engineering, Nanchang University, Nanchang 330031, China)

Abstract

As one of the important methods to protect information security, steganography can ensure the security of data in the process of information transmission, which has attracted much attention in the information security community. However, many current steganography algorithms are not sufficiently resistant to recent steganalysis algorithms, such as deep learning-based steganalysis algorithms. In this manuscript, a new steganography algorithm, based on residual networks and pixel shuffle, is proposed, which combines image encryption and image hiding, named Resen-Hi-Net, an algorithm that first encrypts a secret image and then hides it in a carrier image to produce a meaningful container image. The proposed Resen-Hi-Net has the advantages of both image encryption and image hiding. The experimental results showed that the proposed Resen-Hi-Net could realize both image encryption and image hiding; the visual container image quality was as high as 40.19 dB on average in PSNR to reduce the possibility of being attacked, and the reconstructed secret image quality was also good enough (34.39 dB on average in PSNR). In addition, the proposed Resen-Hi-Net has a strong ability to resist destructive attacks and various steganographic analyses.

Suggested Citation

  • Xishun Zhu & Zhengliang Lai & Nanrun Zhou & Jianhua Wu, 2022. "Steganography with High Reconstruction Robustness: Hiding of Encrypted Secret Images," Mathematics, MDPI, vol. 10(16), pages 1-19, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:2934-:d:888234
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    References listed on IDEAS

    as
    1. Jiaohua Qin & Jing Wang & Yun Tan & Huajun Huang & Xuyu Xiang & Zhibin He, 2020. "Coverless Image Steganography Based on Generative Adversarial Network," Mathematics, MDPI, vol. 8(9), pages 1-11, August.
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    Cited by:

    1. Zhongyun Hua & Yushu Zhang, 2023. "Preface to the Special Issue on “Mathematical Methods for Computer Science”," Mathematics, MDPI, vol. 11(16), pages 1-3, August.

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