## 4 Comparative Results
### Robustness Against Tampering Attack  
This section evaluates the robustness of the proposed technique against tampering attacks. As shown in Figure 8, the extracted secret image demonstrates the effects of tampering on the carrier video segment. The relationship between capacity, robustness, and quality can be visualized as a trade-off triangle; enhancing one aspect negatively impacts the other two. Typically, watermarking schemes prioritize the robustness-quality trade-off, whereas steganography schemes focus on the capacity-quality trade-off. Although the proposed technique primarily aims to embed large secret messages while maintaining a satisfactory carrier quality, the robustness tests indicate that it performs acceptably in comparison to the significantly high capacity ratio achieved by the proposed Octree technique. The first test to be performed in this section is to explore the quality of the extracted image without performing attacks on the carrier signal. Figure 9 shows the PSNR values between the recovered image and the original secret image (orange curve), and the PSNR values between host and carrier video segments (blue curve) when testing using a range of scaling factors k = [1:100]. Figure 9 clearly shows that the extraction quality is affected by the scaling factor \(k\). Based on Figure 9, reducing the scaling factor \(k\) enhances the carrier quality. The reason is that the embedding process can be treated as a noise insertion process. Based on Equation (9), increasing the scaling factor \(k\) will reduce the amplitude of the secret signal. Therefore, enhanced carrier quality can be achieved, as shown in Figure 9.  
On the other hand, Figure 9 shows that reducing the value of the scaling factor \(k\) enhances the extraction quality. The justification can be extracted also from Equation (9). By increasing the scaling factor \(k\), the amplitude of the secret signal will be minimized. The carrier video segments are encoded using an 8-bit integer system. However, the DCT domain is usually represented in decimals. Therefore, the inverse DCT (IDCT) will produce a floating-point matrix which later on should be rounded to the nearest integer. If the secret \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Host** & **Frames** & \(C\) & **Scale _k_** & **Capacity (bpp)** & **PSNR (dB)** & **SSIM** & **CCQE (\%)** \\ \hline \multirow{8}{*}{Documentary} & \multirow{8}{*}{37–101} & \multirow{8}{*}{8} & 25 & 12.75 & 36.51 & 0.9719 & 59.99 \\ \cline{3-6}  & & & 50 & 12.75 & 39.95 & 0.9903 & 61.31 \\ \cline{3-6}  & & & 75 & 12.75 & 40.65 & 0.9933 & 61.56 \\ \cline{3-6}  & & & 100 & 12.75 & 40.78 & 0.9941 & 61.61 \\ \cline{3-6}  & & & 25 & 21.61 & 29.09 & 0.9006 & 74.81 \\ \cline{3-6}  & & & 50 & 21.61 & 29.38 & 0.918 & 75.31 \\ \cline{3-6}  & & & 75 & 21.61 & 29.31 & 0.9191 & 75.32 \\ \cline{3-6}  & & & 100 & 21.61 & 29.24 & 0.9186 & 75.3 \\ \cline{3-6}  & & & 25 & 23.63 & 23.92 & 0.717 & 73.13 \\ \cline{3-6}  & & & 50 & 23.63 & 23.85 & 0.7177 & 73.13 \\ \cline{3-6}  & & & 75 & 23.63 & 23.77 & 0.7143 & 73.02 \\ \cline{3-6}  & & & 100 & 23.63 & 23.73 & 0.7118 & 72.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 15: Detailed results of the proposed Octree-hiding technique using the **Documentary fast-motion segment** as the host video segment with different minimum cube sizes. data are rescaled to a low scale, then rounding would destroy the secret image. Figure 9 shows that the range \(k=[10-100]\) is safe for hiding since results are above 20 dB which is an acceptable quality level between images [35]. Figure 8 shows the extraction results after attacking the carrier image with geometric attacks (cropping or data tampering). A data tampering attack is done by removing some part (a cube for example) of the carrier signal (by replacing it with zeros). The percentage that appears in Figure 8 refers to the dimension of the cropping cube with respect to the dimension of the carrier signal.