# A Chaotic Compressive Sensing Based Data Transmission Method for Sensors within BBNs
## 7 Security Analysis
### Correlation Analysis
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{5}{c}{**Pixels from Original Image**} \\ \hline
**Direction** & **Channel r** & **Channel g** & **Channel b** & **Average** \\ \hline horizontal & 0.981740 & 0.944225 & 0.951633 & 0.9591993 \\ vertical & 0.979666 & 0.940694 & 0.948486 & 0.956282 \\ diagonal & 0.979744 & 0.940788 & 0.948652 & 0.956395 \\ \hline \multicolumn{5}{c}{**Pixels from \(Y_{c}\)**} \\ \hline
**Direction** & **Channel r** & **Channel g** & **Channel b** & **Average** \\ \hline horizontal & 0.005781 & 0.004287 & 0.002708 & 0.004259 \\ vertical & 0.034930 & 0.026071 & 0.029472 & 0.030501 \\ diagonal & 0.039611 & 0.030745 & 0.034106 & 0.034821 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Correlation values of adjacent pixels in image football. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{5}{c}{**Pixels from Original Image**} \\ \hline
**Direction** & **Channel r** & **Channel g** & **Channel b** & **Average** \\ \hline horizontal & 0.976468 & 0.962231 & 0.948301 & 0.962333 \\ vertical & 0.983566 & 0.979146 & 0.974502 & 0.979071 \\ diagonal & 0.983607 & 0.979149 & 0.974644 & 0.979133 \\ \hline \multicolumn{5}{c}{**Pixels from \(Y_{c}\)**} \\ \hline
**Direction** & **Channel r** & **Channel g** & **Channel b** & **Average** \\ \hline horizontal & 0.005781 & 0.004287 & 0.002708 & 0.004259 \\ vertical & 0.034930 & 0.026071 & 0.029472 & 0.030501 \\ diagonal & 0.039611 & 0.030745 & 0.034106 & 0.034821 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Correlation values of adjacent pixels in image llama. Figure 8: Correlation values of adjacent pixels of image llama. The first, second, and third columns are drawn based on adjacent pixels from the red, green, and blue channels of the original image, and the fourth, fifth, and sixth columns are drawn based on adjacent pixels of signal \(Y_{c}\). The three rows show the results calculated from horizontal, vertical, and diagonal directions, respectively. The compression rate is 0.7. Figure 10: Correlation values of adjacent pixels of image football. The first, second, and third columns are drawn based on adjacent pixels from the red, green, and blue channels of the original image, and the fourth, fifth, and sixth columns are drawn based on adjacent pixels of signal \(Y_{c}\). The three rows show the results calculated from horizontal, vertical, and diagonal directions, respectively. The compression rate is 0.7. Figure 9: Correlation values of adjacent pixels of image car. The first, second, and third columns are drawn based on adjacent pixels from the red, green, and blue channels of the original image, and the fourth, fifth, and sixth columns are drawn based on adjacent pixels of signal \(Y_{c}\). The three rows show the results calculated from horizontal, vertical, and diagonal directions, respectively. The compression rate is 0.7. Furthermore, we calculate the correlation of the pixels with exactly the same position chosen from the critical section of the original image and from its concealed form, and the results are reported in Table 8. All the values in Table 8 are extremely close to 0, which implies that the correlations of pixels between the original and concealed sections are low. In other words, the critical information in the original image is well protected.