# Automatic Selective Encryption of DICOM Images
## 4 Performance Analysis and Discussion
### Approach I
#### 4.1.3 Time Performance and Discussion
The proposed approaches in [42; 43] employed similar hardware to the one used in Approach I; therefore, it is reasonable to restrict the comparison among these approaches. In study [42], a novel Fast Quaternion Feistel Cipher (F-QFC) for DICOM images was introduced. This approach employs the Feistel network that uses special properties of quaternions to execute rotations of data in 3D space for each cipher iteration. However, F-QFC has major security flaws. Thus, [PERSON] et al. [43] proposed a Secure Quaternion Feistel Cipher (S-QFC) algorithm that employs the concept of a modified Feistel network with modular arithmetic and the rotations of data sequences in 3D space, in order to enhance the security of F-QFC. Both approaches were deployed on Intel i5 processor with 8-bit grayscale DICOM images, and it can be noticed in Table 2 that the multi-region approach is thousands of times faster than F-QFC and S-QFC, due to the complex orientations in the 3D space. Another important work was presented in [33; 44], which were tested on different hardware, and they have been reported here to indicate the processing speed, not for direct comparison. The work presented by [PERSON] et al. [44] combines statistical segmentation with selective encryption to reduce the amount of data that needs to be encrypted using sophisticated encryption methods. Even though the presented approach was tested on a slower processor, it has an average of 44.87 \(\times\) 10\({}^{6}\) bit/s \(\approx\) 5.6 MB/s. Regardless of the hardware limitation in [44], the processing time of the multi-region approach was 18 times faster. The most similar work to the multi-region approaches was presented by [PERSON] et al. [13; 45], in which a GA was employed to estimate regions' sizes within ROI prior to the encryption process. [PERSON] validated the presented approach using an Intel i7 processor which is more powerful than the one used in this paper. Nevertheless, the proposed multi-region approach achieved a much higher encryption speed. The encryption speed of the reported approach in [13] was 0.4 \(\times\) 10\({}^{6}\) bit/s \(\approx\) 0.05 MB/s, which is slower than the work presented in [44] on slower hardware. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Approach** & **Hardware** & **Software** & **File Size** & **Encryption** & **Decryption** & **Encryption** & **Encryption** \\  & & & & **Time** & **Time (s)** & **Speed (pixel/s)** & **Speed (bit/s)** \\ \hline Statistical Selective & Intel Core 2 & MATLAB & & & & & \\ Selective & Duo, 3 GHZ & R2013b & 512 \(\times\) 512: & & & & \\ Approach [44] & CPU, 2 GB & and Microsoft & 0.26 MB & 0.0468 & – & 5.6 \(\times\) 10\({}^{6}\) & 44.87 \(\times\) 10\({}^{6}\) \\  & RAM Intel & Windows 7 & & & & & \\ \hline Secure Quaternion & Intel(R) & MATLAB & & & & & \\ Fesistel Cipher & i5-3570 CPU @ & & & & & & \\ (S-QFC) & 3.40 GHz, & & & & & & \\ (43) & 16 GB RAM & & & & & & \\ \hline Fast Quaternion & Intel(R) & MATLAB & & & & & \\ (Fesistel Cipher & i5-3570 CPU @ & & & & & \\ (F-QFC) [42] & 3.40 GHz, & & & & & & \\ (6 GB RAM) & & & & & & \\ \hline Adaptive multi-region & Intel i7-820, & & MATLAB 7.10 & 512 \(\times\) 512: & & & \\  & CPU @ 3.40 & & & & 0.52 MB & 10.63 & – & 0.0246 \(\times\) 10\({}^{6}\) \\ encryption & GHz, 16 GB & Windows 7 & & (16-bit depth) & & & \\ \hline  & Intel(R) & & & & & & \\ Proposed & Core(TM) & Cython, & & & & & \\  & i5-3570 CPU @ & & & & & & \\  & 3.40 GHz, & & & & & \\  & 16 GB RAM & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Brief comparison of the encryption time with approaches reported in the literature.