experienced a malicious ransom-ware attack. Obviously, this situation had a negative impact on the government information system security level, including damage to public perception of the government's use of biometric data as mentioned in [2]. As a direct consequence of recent incidents, there is growing interest in developing reliable, versatile, and scalable authentication mechanisms to provide stricter control on all levels of the security chain and improve authentication capabilities in network architecture and standalone systems. One of the best solutions, which can be adopted to mitigate these threats and defend against unauthorized access, is the complementary association and implementation of two or more factors of authentication, based on \"something you are\", \"something you have\", or \"something you know\" [3]. To accomplish the goal of improving authentication systems, an innovative and optimized technical solution for authentication is designed and proposed in this paper, by interconnecting the biometric component (\"something you are\") and the cryptographic component (\"something you have\"), two promising factors that play a pivotal role in securing information in contemporary access control systems. According to [4], the general technical requirements for digital identity proofing and enrollment are described and classified into three main identity assurance levels to validate user genuineness and accuracy; the present mechanism of authentication, which comprises biometric factors and cryptographic algorithms, corresponds to Identity Assurance Level 3, which imposes the strongest conditions for authentication. The main reason for choosing the implementation of the biometric component arises from the fact that real-time facial detection and recognition represent an active area of research, a complex, contactless, and non-intrusive factor for identification and authentication, based on the unique physical characteristics of the individual, which minimizes the risk of someone else using an unauthorized identity and also provides the accuracy and efficiency of the identity process. Despite its several drawbacks, which have been presented in the literature as described in [5; 6], face detection is a mature and reliable technique, with great potential for development if it is associated with the right technology, such as liveness detection, thermal recognition, 3D-three-dimensional shape and infrared technology, machine learning, deep learning, block-chain, or cryptographic algorithms that can be integrated into real-world scenarios of network architecture and seriously enhance the level of security of a system. Therefore, the security of the authentication mechanism is improved by using an additional authentication factor represented by a fully homomorphic cryptographic algorithm, an outstanding and cutting-edge technology with a strong foundation that relies on public and private keys and allows computation over encrypted data without revealing sensitive data and without degrading the accuracy of the processed information. The objective of this factor is to encrypt the facial biometric database stored on the external device, with the purpose of ensuring user privacy according to the principles of processing personal data imposed by the European Union General Data Protection Regulation (GDPR) [7], California Consumer Privacy Act (CCPA), and Health Insurance Portability and Accountability Act (HIPAA), which strictly stipulates special cases and purposes when biometric data can be processed or any other available regulation or standard designated for information security. The present article focuses on research contributions that are developed in two main directions as follows:  
1.