Steganography with High Reconstruction Robustness: Hiding of Encrypted Secret Images
Abstract
:1. Introduction
2. Related Work and Evaluation Indexes
2.1. Residual Convolutional Neural Network (RCNN)
2.2. Pixel Shuffle
2.3. Image Encryption Algorithm
2.4. Evaluation Indexes
3. The Proposed Resen-Hi-Net
3.1. Hiding Network
3.2. Recovery Network
4. Experimental Results
4.1. Developmental Environment and Dataset
4.2. Training Process
4.3. Results of Image Hiding and Recovery
4.4. Performance of Resistance to Cropping and Noise Attacks
4.5. Performance of Resistance to Cropping and Compression Attacks
4.6. Resistance to Steganalyses
4.7. Ablation Study
4.8. Comparison with Other State-of-the-Art CNN Steganography Approaches
5. Conclusions and Discussion
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Image Group | Container vs. Carrier PSNR (dB), MSSIM, MSE | Reconstructed vs. Secret PSNR (dB), MSSIM, MSE | Container vs. Carrier APE (R, G, B) | Reconstructed vs. Secret APE (R, G, B) |
---|---|---|---|---|
a | 39.67, 0.99, 14.76 | 35.34, 0.96, 35.98 | 0.75, 0.78, 0.76 | 3.34,3.70, 3.73 |
b | 40.51, 0.99, 10.78 | 32.30, 0.92, 114.91 | 0.45, 0.46, 0.55 | 5.29, 5.47, 6.32 |
c | 40.22, 0.99, 11.34 | 35.29, 0.97, 45.86 | 0.53, 0.52, 0.54 | 3.91, 4.12, 4.58 |
d | 40.34, 0.99, 12.31 | 34.61, 0.96, 53.57 | 0.64, 0.67, 0.66 | 4.00, 4.19, 4.61 |
Average | 40.19, 0.99, 12.29 | 34.39, 0.95, 62.58 | 0.59, 0.61, 0.63 | 4.14, 4.37, 4.81 |
Attack Mode | Attack Intensity | PSNR | MSSIM | MSE | APE (R, G, B) |
---|---|---|---|---|---|
Gaussian noise attack (power/dBW) | 0.01 | 27.17 | 0.893 | 373 | 8.23, 7.88, 8.30 |
0.04 | 26.75 | 0.875 | 415 | 8.87, 9.09, 9.52 | |
0.08 | 26.56 | 0.869 | 412 | 9.70, 8.60, 8.89 | |
0.12 | 26.31 | 0.857 | 455 | 9.85, 9.53, 9.84 | |
Salt and pepper noise attack (power/dBW) | 0.01 | 28.41 | 0.900 | 281 | 7.32, 7.22, 7.50 |
0.05 | 27.86 | 0.893 | 320 | 7.77, 8.05, 8.41 | |
0.1 | 27.43 | 0.887 | 418 | 8.10, 8.27, 8.55 | |
0.2 | 25.03 | 0.863 | 612 | 9.51, 8.53, 9.06 |
Attack Mode | Attack Intensity | PSNR (dB) | MSSIM | MSE | APE(R,G,B) |
---|---|---|---|---|---|
Cropping attacks (pixels) | 10 × 10 | 31.98 | 0.963 | 126 | 3.43,3.33,3.53 |
25 × 30 | 28.73 | 0.913 | 217 | 5.23,5.67,5.15 | |
Two of 25 × 30 | 25.56 | 0.844 | 588 | 9.98,9.08,10.56 | |
Three of 25 × 30 | 25.12 | 0.832 | 751 | 11.89,11,34,12.20 | |
PCA compression (compression ratio) | 1.53 | 24.32 | 0.835 | 1237 | 16.72,17.66,17.60 |
2.98 | 23.14 | 0.822 | 1594 | 18.81,18.73,19,21 | |
5.88 | 21.51 | 0.806 | 1874 | 21.14,22.84,22.83 | |
11.77 | 20.63 | 0.783 | 2325 | 22.36,24.21,24.27 |
Container vs. Carrier | Reconstructed vs. Secret | AUC | |||||
---|---|---|---|---|---|---|---|
PSNR (dB) | MSSIM | PSNR (dB) | MSSIM | SRM | MaxSRM | Ye-Net | |
1 | 37.98 | 0.973 | 37.68 | 0.971 | 0.67 | 0.76 | 0.81 |
0.8 | 38.73 | 0.978 | 36.42 | 0.968 | 0.66 | 0.73 | 0.79 |
0.6 | 39.16 | 0.984 | 36.13 | 0.964 | 0.63 | 0.69 | 0.76 |
0.4 | 39.75 | 0.988 | 35.53 | 0.963 | 0.57 | 0.63 | 0.73 |
0.2 | 40.60 | 0.993 | 34.23 | 0.960 | 0.51 | 0.58 | 0.69 |
0.1 | 41.39 | 0.994 | 32.07 | 0.952 | 0.51 | 0.57 | 0.64 |
Methods | Container vs. Carrier | Reconstructed vs. Secret | Against Steganalysis (AUC) | ||||||
---|---|---|---|---|---|---|---|---|---|
PSNR (dB) | MSSIM | APE (R,G,B) | PSNR (dB) | MSSIM | APE (R,G,B) | SRM | MaxSRM | Ye-Net | |
Baluja-Net [34] | 36.49 | 0.95 | 0.48, 0.49, 0.43 | 30.56 | 0.90 | 4.79, 4,37, 4.53 | 0.63 | 0.72 | 0.79 |
ISN [35] | 39.28 | 0.977 | N/A | 40.42 | 0.985 | N/A | 0.59 | 0.65 | 0.73 |
Proposed Resen-Hi-Net | 40.13 | 0.983 | 0.45, 0.46, 0.44 | 34.25 | 0.951 | 3.95, 4.34, 4.46 | 0.51 | 0.58 | 0.69 |
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Zhu, X.; Lai, Z.; Zhou, N.; Wu, J. Steganography with High Reconstruction Robustness: Hiding of Encrypted Secret Images. Mathematics 2022, 10, 2934. https://doi.org/10.3390/math10162934
Zhu X, Lai Z, Zhou N, Wu J. Steganography with High Reconstruction Robustness: Hiding of Encrypted Secret Images. Mathematics. 2022; 10(16):2934. https://doi.org/10.3390/math10162934
Chicago/Turabian StyleZhu, Xishun, Zhengliang Lai, Nanrun Zhou, and Jianhua Wu. 2022. "Steganography with High Reconstruction Robustness: Hiding of Encrypted Secret Images" Mathematics 10, no. 16: 2934. https://doi.org/10.3390/math10162934
APA StyleZhu, X., Lai, Z., Zhou, N., & Wu, J. (2022). Steganography with High Reconstruction Robustness: Hiding of Encrypted Secret Images. Mathematics, 10(16), 2934. https://doi.org/10.3390/math10162934