# High-Fidelity Steganography: A Covert Parity Bit Model-Based Approach
## 4 Proposed Scheme
### Data Embedding
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Coefficient**} & \multicolumn{3}{c}{**Proposed**} \\ \cline{3-8}  & & & **Replacement** & & & \\ \hline
**Block Size** & **Capacity** & **Cover** & **PSNR** & **SSIM** & **PSNR** & **SSIM** & **Cost** \\ \hline \multirow{4}{*}{400 \(\times\) 400} & \multirow{4}{*}{14.65} & Airplane & 41.80 & 0.9857 & 45.09 & 0.9858 & 4.00\% \\ \cline{3-8}  & & Animal & 25.40 & 0.9945 & 31.20 & 0.9973 & 4.00\% \\ \cline{3-8}  & & Vegetables & 31.45 & 0.9947 & 37.67 & 0.9963 & 4.00\% \\ \hline \multirow{4}{*}{425 \(\times\) 425} & \multirow{4}{*}{16.54} & Airplane & 40.02 & 0.9845 & 43.23 & 0.9776 & 3.76\% \\ \cline{3-8}  & & Animal & 24.81 & 0.9926 & 29.09 & 0.9964 & 3.76\% \\ \cline{3-8}  & & Vegetables & 29.24 & 0.9926 & 36.56 & 0.9959 & 3.76\% \\ \hline \multirow{4}{*}{450 \(\times\) 450} & \multirow{4}{*}{18.54} & Airplane & 38.91 & 0.9672 & 41.61 & 0.9679 & 3.56\% \\ \cline{3-8}  & & Animal & 23.86 & 0.9895 & 26.88 & 0.9952 & 3.56\% \\ \cline{3-8}  & & Vegetables & 27.22 & 0.9878 & 32.89 & 0.9941 & 3.56\% \\ \hline \multirow{4}{*}{475 \(\times\) 475} & \multirow{4}{*}{20.66} & Airplane & 29.93 & 0.9628 & 38.50 & 0.9562 & 3.37\% \\ \cline{3-8}  & & Animal & 20.74 & 0.9820 & 23.79 & 0.9922 & 3.37\% \\ \cline{3-8}  & & Vegetables & 25.16 & 0.9744 & 30.97 & 0.9906 & 3.37\% \\ \hline \multirow{4}{*}{500 \(\times\) 500} & \multirow{4}{*}{22.89} & Airplane & 23.36 & 0.7913 & 29.10 & 0.9105 & 3.20\% \\ \cline{3-8}  & & Animal & 17.33 & 0.9539 & 19.12 & 0.9813 & 3.20\% \\ \cline{3-8}  & & Vegetables & 18.91 & 0.9560 & 24.07 & 0.9780 & 3.20\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of the proposed hiding scheme (zigzag version) with the coefficient replacement idea in terms of the capacity–transparency trade-off. The capacity is measured using bpp, while the transparency is evaluated using the PSNR values [22] when \(n=15\). ### Robustness

This section provides a robustness evaluation of the proposed method by exploring the quality of the recovered confidential message after attacking the container signal with data loss tampering attacks and noise distribution attacks. In these experiments, the stego image was exposed to two different types of attacks: a \"Salt and Pepper\" attack, and a Tampering (data loss) attack. The salt and pepper attack involved random dispersal of black and white pixels with density \(\mathbf{d}\), where \(0<\mathbf{d}<1\) \begin{table}
\begin{tabular}{l c c} \hline \hline
**Method** & **bpp** & **PSNR (dB)** \\ \hline
[46] & 4.84 & 31.67 \\ \hline
[47] & 3.48 & **41.00** \\ \hline
[45] & **9.60** & **48.84** \\ \hline
[20] & **12.18** & 34.03 \\ \hline
[16] (_Max. dB_) & 15.17 & 35.00 \\ \hline
[38] & 1.50 & 25.00 \\ \hline
[5]: CF-FB-GAR (_Max. dB_) & **19.54** & 35.03 \\ \hline
[5]: CF-QTAR (_Max. dB_) & **19.88** & 35.02 \\ \hline
[19] & **19.50** & 32.00 \\ \hline
[36] & 6.00 & 45.34 \\ \hline Proposed Scheme \(n=2\) & **18.54** & **41.84** \\ \hline Proposed Scheme \(n=15\) & **18.54** & **42.41** \\ \hline Proposed Scheme \(n=15-zigzag\) & **18.54** & **41.61** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of the maximum bpp and PSNR values for different _high stego quality_ methods. The highest bpp and PSNR values are highlighted in bold. \begin{table}
\begin{tabular}{l c c} \hline \hline
**Method** & **bpp** & **PSNR (dB)** \\ \hline
[48] & **14.38** & 26.20 \\ \hline
[18] & **20.22** & 25.00 \\ \hline
[41] & **20.83** & 27.00 \\ \hline
[16] (_Max. bpp_) & **21.01** & 27.00 \\ \hline
[5] CF-FB-GAR (_Max. bpp_) & **22.43** & 28.49 \\ \hline
[5] CF-QTAR (_Max. bpp_) & **22.70** & 28.15 \\ \hline
[19] (_Max. bpp_) & **19.30** & **29.10** \\ \hline
[19] (_Max. bpp_) & **19.50** & **32.00** \\ \hline Proposed Scheme \(n=2\) & **22.89** & **30.22** \\ \hline Proposed Scheme \(n=15\) & **22.89** & **32.91** \\ \hline Proposed Scheme \(n=15-zigzag\) & **22.89** & **29.10** \\ \hline \hline \end{tabular}
\end{table}