Year: 2026
Type: article
Abstract: 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.
Language: English
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
SDG: Reduced inequalities
Open Access status: diamond
OpenAlex ID: W7217013271