The development of national digital identity systems has sped up, leading to an increasing demand for biometric authentication system, which needs to be secure and able to serve all users and be adapted to future needs. The classical biometric systems rely on fingerprints, iris scans and facial recognition technology, which poses significant accessibility challenges to individuals with physical disabilities, visual impairments and atypical biometric characteristics such as those born without fingers or having more fingers. The existing protocols are vulnerable to the new quantum attacks that threaten classical cryptographic protocols. This work presents the Quantum-Resilient Inclusive Biometric Framework, which allows the use of various biometrics and resilient to quantum threats. The framework supports matching via a quantum state encoding method which encodes multiple biometric features under a Grover-based search technique that amplifies the amplitudes. We present a smart identity card system which can be proved to be post-quantum secure by combining lattice-based cryptography and quantum-safe digital signatures. The architecture is such that offering access to the chip-enabled authentication and Braille-assisted verification system doesn't compromise the security of the cryptographic protections. Security is evaluated by calculating quantum threat models with Shor-type, Grover-type attacks as potential adversary techniques. The proposed model offers better scalability for large-scale biometric search, as well as it offers better accessibility to the disabled people and better privacy and security in facing cyber threats that will be evolved by quantum technologies in the future. The work builds a secure and affordable national identity infrastructure through design of national identity systems based on quantum computing principles for the inclusive biometric systems.
The development of national digital identity systems has sped up, leading to an increasing demand for biometric authentication system, which needs to be secure and able to serve all users and be adapted to future needs. The classical biometric systems rely on fingerprints, iris scans and facial recognition technology, which poses significant accessibility challenges to individuals with physical disabilities, visual impairments and atypical biometric characteristics such as those born without fingers or having more fingers. The existing protocols are vulnerable to the new quantum attacks that threaten classical cryptographic protocols. This work presents the Quantum-Resilient Inclusive Biometric Framework, which allows the use of various biometrics and resilient to quantum threats. The framework supports matching via a quantum state encoding method which encodes multiple biometric features under a Grover-based search technique that amplifies the amplitudes. We present a smart identity card system which can be proved to be post-quantum secure by combining lattice-based cryptography and quantum-safe digital signatures. The architecture is such that offering access to the chip-enabled authentication and Braille-assisted verification system doesn't compromise the security of the cryptographic protections. Security is evaluated by calculating quantum threat models with Shor-type, Grover-type attacks as potential adversary techniques. The proposed model offers better scalability for large-scale biometric search, as well as it offers better accessibility to the disabled people and better privacy and security in facing cyber threats that will be evolved by quantum technologies in the future. The work builds a secure and affordable national identity infrastructure through design of national identity systems based on quantum computing principles for the inclusive biometric systems.
Biometric authentication has become integral to digital identity systems, particularly in smart cities where it enables secure access to services across governance, transportation, and public infrastructure. Centralised architectures, though widely used, pose privacy and scalability challenges due to the aggregation of sensitive biometric data. Decentralised identity frameworks offer better data sovereignty and eliminate single points of failure but introduce new security concerns, particularly around mutual trust among distributed devices. In such environments, biometric sensors and verification agents must authenticate one another before sharing sensitive biometric data. Existing authentication schemes rely on classical public key infrastructure, which is increasingly susceptible to quantum attacks. This work addresses this gap by proposing a quantum-secure communication protocol for decentralised biometric systems, built upon an enhanced Quantum Key Distribution (QKD) system. The protocol incorporates quantum-resilient authentication at both the classical and quantum layers of QKD: post-quantum cryptography (PQC) is used to secure the classical channel, while authentication qubits verify the integrity of the quantum channel. Once trust is established, QKD generates symmetric keys for encrypting biometric data in transit. Qiskit-based simulations show a key generation rate of 15 bits/sec and 89% efficiency. This layered, quantum-resilient approach offers scalable, robust authentication for next-generation smart city infrastructures.
Biometric authentication has become integral to digital identity systems, particularly in smart cities where it en-ables secure access to services across governance, trans-portation, and public infrastructure. Centralised archi-tectures, though widely used, pose privacy and scalabil-ity challenges due to the aggregation of sensitive biomet-ric data. Decentralised identity frameworks offer better data sovereignty and eliminate single points of failure but introduce new security concerns, particularly around mu-tual trust among distributed devices. In such environments, biometric sensors and verification agents must authenticate one another before sharing sensitive biometric data. Ex-isting authentication schemes rely on classical public key infrastructure, which is increasingly susceptible to quan-tum attacks. This work addresses this gap by propos-ing a quantum-secure communication protocol for decen-tralised biometric systems, built upon an enhanced Quan-tum Key Distribution (QKD) system. The protocol incorpo-rates quantum-resilient authentication at both the classical and quantum layers of QKD: post-quantum cryptography (PQC) is used to secure the classical channel, while authen-tication qubits verify the integrity of the quantum channel. Once trust is established, QKD generates symmetric keys for encrypting biometric data in transit. Qiskit-based sim-ulations show a key generation rate of 15 bits/sec and 89% efficiency. This layered, quantum-resilient approach offers scalable, robust authentication for next-generation smart city infrastructures.
The rapid progress of quantum computing now poses a substantial security risk to the information infrastructures of various nations, which are fundamentally reliant on classical cryptographic systems. Encryption algorithms such as RSA, ECC, and, notably, Satyamani’s, Shor, and Grover algorithms are vulnerable to quantum attacks; indeed, these algorithms can compromise code creation and encryption protocols within seconds when subjected to powerful quantum computing devices. In response to this emerging threat, this paper presents the design and evaluation of a quantum-resilient cryptographic protocol suite intended for national information systems security. The proposed version integrates lattice-based key exchange and hash-based digital signatures, rendering it post-quantum and compatible with the existing Public Key Infrastructure (PKI) and network protocol stack. Formal security analysis and performance evaluation were conducted using simulated nationwide network environments. Experimental results demonstrate that the proposed scheme achieves a computational latency reduction of up to 45% compared to baseline post-quantum algorithms, while maintaining high resilience against both classical and quantum adversaries. The scalability test indicates that quantum-resilient cryptography can be deployed across various government apparatuses, promoting national cybersecurity and digital autonomy, while maintaining security and interoperability
Healthcare systems are rapidly becoming digital, which has increased the demand for safe, dependable, and privacy-preserving authentication methods. Iris biometrics have emerged as a key component for identity verification in delicate settings due to their high accuracy and stability. However, protecting privacy and data security is a difficulty for conventional biometric systems, particularly in light of new quantum risks. For advanced healthcare security, this study suggests a revolutionary quantum-enhanced, privacy-preserving iris biometrics system. Through the integration of quantum computing technologies, the framework makes use of quantum-accelerated algorithms like Grover's algorithm for efficient template matching and quantum-safe cryptography like Quantum Key Distribution (QKD). Homomorphic encryption and federated learning are two further ways to improve privacy preservation while guaranteeing adherence to HIPAA and other healthcare data protection laws. In comparison to conventional techniques, the suggested system performs better in terms of accuracy, security, and computational efficiency when tested on benchmark iris datasets. By filling important gaps in safe and privacy-focused identity management, this research creates a novel method at the nexus of quantum computing, biometrics, and healthcare.
The digital banking ecosystem faces unprecedented security challenges with the imminent advent of quantum computing, which threatens to compromise existing cryptographic infrastructures. Traditional multi-factor authentication (MFA) systems in banking rely on classical cryptographic primitives vulnerable to quantum attacks, creating critical security gaps in financial transactions and customer data protection. This paper introduces a novel Quantum-Enhanced Multi-Factor Authentication Framework (QE-MFAF) specifically designed for digital banking systems, integrating lattice-based post-quantum cryptography with biometric fuzzy commitment schemes and behavioral analytics. The proposed framework incorporates a hybrid authentication mechanism combining quantum-resistant cryptographic protocols, continuous behavioral pattern recognition using deep learning models, and secure multi-party computation for transaction verification. Experimental validation on a synthetic banking dataset demonstrates superior performance with 99.7% authentication accuracy, 0.02% false positive rate, and 15ms average authentication latency while maintaining quantum resistance. The framework successfully mitigates advanced persistent threats, insider attacks, and quantum-based cryptographic vulnerabilities while ensuring seamless user experience in high-transaction banking environments. Performance comparisons with existing banking authentication systems show 34% improvement in security metrics and 28% reduction in computational overhead.
Quantum computing is based on the principles of quantum mechanics and uses quantum bits (qubits) that can exist in a state of superposition and entanglement. They promise a revolution in computing and information security. Firstly, using quantum algorithms in information technology opens up new possibilities for processing and protecting data. Secondly, biometric information security relies on a person's unique physical and behavioural characteristics, such as fingerprints, facial recognition, iris, voice, and others. These methods provide a high level of security due to their uniqueness and difficulty in counterfeiting. Combining the principles of quantum computing and biometric information security allows us to identify their similarities and integration capabilities to create reliable systems for protecting confidential information. While previous research in biometric information security has focused on individual aspects of decision-making to ensure the information security of educational institutions when using facial recognition technologies, this work presents a comprehensive framework combining several components into a single unified system for using various quantum cryptography algorithms. The main advantages of using quantum computing in object and image detection include accelerating the computational process using quantum components, robustness at different object angles, suitability for moving or static conditions, cryptographic noise immunity, and the ability to work in real practical conditions. The advantages of the quantum cryptographic scheme for face recognition technologies include ease of implementation, high cryptography security, the ability to parallelise the processes of encoding and decoding images, and the fact that complex computer equipment is not required. The study results provide a solid foundation for developing hybrid quantum computing and biometric information security technologies. Using the possibility of hybrid computing opens up new horizons for the standardisation and public dissemination of new technologies, and such a combination ensures reliable protection of confidential information and stimulates further research aimed at improving data protection methods in the context of the rapid development of the digital world.