## 5 Performance Analysis and Results
### Visual Quality Metrics  
Remarkable indicators used in studying the encryption robustness are represented as the Key Performance Indicators (KPIs) for the proposed system. Visual quality inspection is measured in terms of \(BER\) performance and PSNR as a clarity investigation performance as well as statistical measures to evaluate the degree of encryption quantitatively. The visual quality metrics for the proposed scheme are measured in terms of BER performance and \(PSNR\) performance in the form \(E_{b}N_{0}\)vs.\(BER\), and \(E_{b}N_{0}\)vs.\(PSNR\) as a visual testing for the received image. Different \(E_{b}N_{0}\) values between 0 and 18 dB are used to calculate the \(PSNR\) values of the received image. Bit Error Rate (BER) is a signal quality metric that evaluates the performance of the entire system, including the transmitter, the receiver, and the medium used to connect them. \(BER\) is defined as the ratio of the number of bits received in error due to interference, noise, or other problems to the total number of bits received. In [24], the \(BER\) simple formula is defined. \[BER=\frac{\text{Number of bit errors}}{\text{Total number of transferred bits}} \tag{25}\]  
\[PSNR=10\times log_{10}\frac{f_{max}^{2}\times M\times N}{\sum_{i=1}^{M}\sum_{j= 1}^{N}(I(i,j)-I^{\prime}(i,j))^{2}} \tag{26}\]  
The \(PSNR\) ratio, which is measured in decibels (dB), is regarded as a visual quality metric test of the reconstructed (decrypted) image compared to the original transmitted image [25]. The quality of the produced image will be better the higher the \(PSNR\) value. Here, \(f_{max}^{2}\) denotes the highest pixel value possible, \(I(i,j)\) denotes the original image pixel, \(I(i,j)\) denotes the received image pixel values, (\(M\times N\)) denotes the image size, and all other variables are equal. Various images with a resolution of \(256\times 256\) pixels are used to test the simulation analysis for the proposed authenticated secure image transfer technique. The AWGN channel is a well-known model to indicate various random processes seen in nature; it contains a uniform power across the whole frequency band. Starting with a CT brain medical image, the proposed system behavior is examined under the AWGN channel effect at zero mean \(\mu=0\) and over certain ranges of noise variances, \(\left(\sigma^{2}=0.01,0.05,0.10,0.15,0.20\right)\), as shown in Table 4. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Gray-Scale Image** & **Size** & **256\(\times\)256** \\ \hline \multirow{3}{*}{Channel coding} & Type & Convolutional Encoder \\ \cline{2-3}  & Code Rate & 1/2 \\ \hline \multirow{3}{*}{OFDM parameters} & Sub-carrier (\(N_{sc}\)) & 256 \\ \cline{2-3}  & FFT length & 256 \\ \cline{2-3}  & Cyclic prefix (CP) & 32 \\ \hline \multirow{3}{*}{Attacks} & AWGN & \(\left(\sigma^{2}=0.01,\ 0.05,\right)\) \\ \cline{2-3}  & Salt and Pepper noise & \(\left(\sigma^{2}=0.02\right)\) \\ \cline{2-3}  & Speckle noise & \(\left(\sigma^{2}=0.02\right)\) \\ \hline \multirow{3}{*}{Key Performance Indicators (KPI)} & Visual Quality Metrics (Clarity investigation) & \(E_{b}N_{0}\) vs.\(BER\) \(E_{b}N_{0}\) vs.\(PSNR\) \(E_{b}N_{0}\) vs.\(PSNR\) \\ \cline{2-3}  & & \(NPCR\) \\ \cline{1-1} \cline{2-3}  & Encryption Quality Metrics (Statistical Analysis) & \(UAC1\) \\ \cline{1-1} \cline{2-3}  & & \(r_{xy}\), Histogram, Key space \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The proposed authenticated secure image transmission system simulation parameters. A Salt and Pepper noise attack is when a certain amount of the pixels in the image are affected by an impulse type of noise represented by either black or white dots (hence the name of the noise), which can significantly deteriorate the quality of an image [3]. It can be used to model defects in the transmission of the image. The proposed authenticated secure image transmission scheme system is examined under Salt and Pepper noise attack; here, the noise density \(d=0.02\).