## 5 Conclusions  
The emergent development of new technologies in biometrics and cryptography has provided new opportunities for enhancing information security in different types of applications. The objective of this research is to integrate and capitalize on the great potential of these powerful techniques to create a real experimental environment for user authentication and also to control remotely the entire resources involved in the authentication process and protect them against attack vectors.  
Therefore, in this study, we succeeded in developing two main directions that were established at the beginning of our work, so we designed a cost-effective technical solution for authentication in different standalone systems and network devices using facial biometrics for detection and recognition combined with fully homomorphic encryption, a relatively complex and compact system based on Raspberry Pi and Arduino modules. These modules offer several advantages, including reasonable acquisition costs, a user-friendly interface, flexibility, and versatility in developing custom solutions. This mechanism can be deployed in different scenarios where the need to ensure user confidentiality is very high. However, it is important to highlight some drawbacks associated with fully homomorphic encryption. One of these drawbacks is the need to ensure powerful computation resources to obtain an optimized time for information encryption and decryption.  
The statistical measurements that were carried out, over the biometric facial database using the BFV and the BGV homomorphic encryption algorithms, provided a deeper understanding of biometric encryption status and helped us to identify the best alternative for enhancing storage security and optimizing the system capabilities, thus proving its performance and superiority in improving overall security.  
In summary, the novelty of the proposed approach lies in the design of a multi-factor authentication mechanism, a closed system with restricted access based on the system-on-device architecture that performs real-time user authentication and provides a user-friendly web interface for remote administration.  
The future development directions to improve the level of security and user accuracy in the authentication process would be the implementation of an additional factor based on iris features, to create a multimodal mechanism, and also the improvement of the facial and iris recognition algorithm structure by using deep learning and convolutional neural network (CNN) algorithms. Finally, the optimization of the encryption algorithm to minimize the noise level and keep it below a certain limit favorable to perform efficient and timely encryption and also to enhance the execution time would be a mandatory direction.  
Conceptualization, L.D. and G.C.; methodology, G.C. and M.V.C.; software, G.C.; validation, G.C.; formal analysis, G.C. and L.D.; investigation, G.C. and M.V.C.; resources, G.C.; data curation, G.C.; writing--original draft preparation, G.C.; writing--review and editing, G.C. and M.V.C.; visualization, G.C.; supervision, L.D.; project administration, L.D. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Informed Consent StatementInformed consent was obtained from all subjects involved in the study.  
The authors confirm that the data supporting the findings of this study are available within the article.  
The authors declare no conflicts of interest.