# A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices
## 4 Results and Comparisons
### Visual Results Analysis
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Metric** & **Definition and Recommended Value (Cover/Stego)** & **Optimal Value** \\ \hline Mean Square Error (MSE) [42] & Calculate error percentage between cover and stego frames. Low MSE value is recommended. & 0 \\ \hline Peak Signal-to-Noise Ratio (PSNR) (dB) [43] & Measure the quality of the stego frame referring to the cover frame. High value is recommended. & \textgreater{}20 dB \\ \hline Signal-to-Noise Ratio (SNR) (dB) [44] & Estimate the average power of the cover frame referring to the one of the difference between the stego and cover frames. High value is recommended. & \textgreater{}20 dB \\ \hline Weighted Signal-to-Noise Ratio (WSNR) (dB) [45] & Determine the amount of average weighted power of the cover frame referring to the one of the difference between the stego and cover frames. High value is recommended. & \textgreater{}20 dB \\ \hline Noise Quality Measure (NQM) (dB) [46] & Estimate the amount of distortion in terms of local luminance, contrast perception, and frequency shift between the stego and cover video frames. High value is recommended. & \textgreater{}20 dB \\ \hline Structural Content (SC) [47] & Estimate the amount of power for the cover frame referring to the amount of power for the stego frame. Low value is recommended. & \textgreater{}1 \\ \hline Maximum Difference (MD) [48] & Estimate the difference between the stego and cover frames. Low value is recommended. & \textgreater{}5 \\ \hline Normalized Absolute Error (NAE) [43] & Estimate the absolute difference value between the stego and cover video frames referring to the absolute value of the cover frame. Low value is recommended. & 0 \\ \hline Laplacian Mean Square Error (LMSE) [48] & Determine the edges difference between stego and cover frames. Low value is recommended. & 0 \\ \hline Structural Similarity Index (SSIM) [49] & Assees the visual structural similarity between the stego and cover frames. High value is recommended. & 1 \\ \hline Multi-Scale SSIM index (MS-SSIM) [50] & Evaluate the multi-scale structural similarity between the stego and cover frames. High value is recommended. & 1 \\ \hline Feature Similarity Index (PSIM) [51] & Estimate the feature similarity between the stego and cover frames. High value is recommended. & 1 \\ \hline Universal Quality Index (UQI) [52] & Evaluate the universal not local similarity in terms of correlation/contrast/luminance quantities between the stego and cover video frames. High value is recommended. & 1 \\ \hline Normalized Cross Correlation (NK) [53] & Compare the stego frame with the reference cover frame. High value is recommended. & 1 \\ \hline Average Difference (AD) [54] & Estimate the average difference between cover and stego frames. Low value is recommended. & 0 \\ \hline Pixel-based Visual Information Fidelity (VIFP) [55] & Compare the similarity information of pixels content of the stego and cover frames. High value is recommended. & 1 \\ \hline Bit Error Rate (BER) [41] & Estimate the pixel error rate between the stego and cover frames. Low value is recommended. & 0 \\ \hline Edge detection ratio (EDR) [48] & Determine the Gaussian Laplacian difference at the edges. Low value is recommended. & 0 \\ \hline Entropy (E) [48] & Estimate the amount of information in the video frame. It is recommended to get a lower value of difference entropy between the cover/stego frames (\(\Delta E\)). & (\(\Delta E\)) = 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The employed visual objective quality assessment metrics.