# A Medical Image Encryption Scheme for Secure Fingerprint-Based Authenticated Transmission
## 5 Conclusions  
A visually secure image encryption scheme with fingerprint-based authentication has been proposed to ensure integrity, authenticity, and confidentiality during medical image transmission. A watermarking process ensures visual security by embedding a medical image into a non-significant reference image to achieve a visually meaningful encrypted image without compromising its visual quality. In addition, an encryption scheme based on random mapping and a random permutation key has been implemented to protect the medical image and fingerprint features and ensure security against white-box attacks. Simulation results show high mean PSNR values of 54.947 dB between the original and reconstructed medical images. However, the distances of histogram intersection between the original reference images and visually meaningful encrypted images are above 0.98. These values demonstrate the quality of the image reconstruction and the visual security of the proposed scheme. Comparison results show that the proposed scheme achieved the best performance in reconstructed image quality compared to other visually secure image encryption schemes.  
On the other hand, the proposed scheme ensured both visual protection and encryption of medical images and the physician's fingerprint, compared with other single-protection approaches. In future work, multimodal biometric data will be used to improve the image authentication process. Moreover, the running time of the proposed scheme can be improved by reducing the data to be embedded using small images.  
Conceptualization, F.C. and D.I; methodology, F.C. and G.P.; software, F.C.; validation, F.C; formal analysis, F.C.; investigation, F.C.; resources, F.C. and D.I; data curation, F.C.; writing--original draft preparation, F.C.; writing--review and editing, F.C. and D.I.; visualization, D.I. and G.P.; supervision, D.I. and G.P.; project administration, D.I. and G.P.; funding acquisition, D.I and G.P. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Medical Image** & **Reference Image** & **Encryption Time (s)** & **Decryption Time (s)** \\ \hline lungs & Barbara & 13.547 & 10.143 \\ pelvic & Lena & 53.109 & 57.433 \\ head & airplane & 3.419 & 6.188 \\ skin & pepper & 3.316 & 3.665 \\ breast & baboon & 4.884 & 4.156 \\ kidney & girl & 4.056 & 3.345 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Encryption and decryption time.  
Funding: FAIR PNRR. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable.  
**Acknowledgments:** [PERSON] is a PhD student enrolled in the National PhD in Artificial Intelligence, XXXVIII cycle, course on health and life sciences, organized by \"Universita Campus Bio-Medico di Roma\". This work is partially supported by the co-funding of the European Union -Next Generation EU: NNRP Initiative, Mission 4, Component 2, Investment 1.3-Partnerships extended to universities, research centres, companies and research D.D. MUR n. 341 del 15.03.2022-Next Generation EU (PE0000013-\"Future Artificial Intelligence Research-FAIR\"-CUP: H97G22000210007).  
**Conflicts of Interest:** The authors declare no conflict of interest.