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Robust coverless image steganography based on DenseUNet with multi-scale feature fusion and attention mechanism

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Abstract

Coverless image steganography (CIS) have attracted considerable attention due to their ability to resist steganalysis detection completely. However, most of the existing CIS methods are weak in robustness to geometric attacks, and it is difficult to achieve a balance between geometric attacks and non-geometric attacks. So, a robust coverless image steganography method based on DenseUNet with multi-scale feature fusion attention mechanism is proposed in this paper. At the sender, an end-to-end hash sequence generation model is designed by combining the DenseUNet network with the multi-scale feature fusion attention mechanism to extract the multi-scale CNN features of the images, and as serve matching benchmarks. Secondly, a hybrid loss function is introduced into the network model for network training to generate hash sequences with robust features. Finally, the secret information is segmented into equal-length segments, and the image whose hash sequence matches the secret information segment is selected as a stego-images using the inverted index. At the receiver, the secret information was recovered from the stego-images using the constructed network model. Experimental results show that the proposed method has stronger performance in terms of robustness and security compared with existing CIS schemes, and achieves enhanced robustness against both the geometric attacks and non-geometric attacks at four different datasets.

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The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 61862041).

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Author notes

  1. Xiaopeng Li, Qiuyu Zhang and Zhe Li contributed equally to this work.

Authors and Affiliations

  1. School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, Gansu, China

    Xiaopeng Li, Qiuyu Zhang & Zhe Li

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  1. Xiaopeng Li
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  2. Qiuyu Zhang
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  3. Zhe Li
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Xiaopeng Li and Zhe Li. The first draft of the manuscript was written by Xiaopeng Li, Qiuyu Zhang commented on previous versions of the manuscript and critically revised the work. All authors read and approved the final manuscript.

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Correspondence to Qiuyu Zhang.

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Li, X., Zhang, Q. & Li, Z. Robust coverless image steganography based on DenseUNet with multi-scale feature fusion and attention mechanism. SIViP 18, 8251–8266 (2024). https://doi.org/10.1007/s11760-024-03468-8

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