Biometrics-Based Information Security

Abstract

The accelerating digitization of human activities has redefined how information is cre- ated, transmitted, and protected. However, this interconnected digital ecosystem has also become a prime target for sophisticated cyberattacks, data breaches, and iden- tity fraud. Traditional security mechanisms, such as passwords, PINs, and centralized databases, are increasingly inadequate to safeguard sensitive assets and personal iden- tities. In this context, biometric-based authentication, supported by emerging technolo- gies, offers a path toward more resilient and user-centered security. This thesis proposes an integrated, multi-layered security framework that unites biometrics, blockchain, ex- plainable artificial intelligence (XAI), and quantum machine learning (QML) to achieve secure, transparent, and future-ready identity verification. The research first introduces a revocable biometric template protection scheme that ensures both privacy and renewa- bility, allowing biometric credentials to be securely reissued if compromised. Building upon this, the MedBioCh system is developed, an innovative blockchain-enabled archi- tecture for digital healthcare that decentralizes trust, prevents tampering, and enforces privacy-aware access control through smart contracts. To strengthen accountability and interpretability, an explainable phase-aware biometric framework is proposed, enabling transparent authentication decisions and traceable reasoning paths suitable for sensitive sectors such as healthcare and justice. Furthermore, a training-free quantum classi- fier based on fidelity-based similarity is designed to deliver efficient, interpretable, and noise-resilient classification, offering a realistic step toward post-quantum security. Ex- perimental evaluations across multiple biometric datasets confirm the frameworks su- perior resilience against spoofing, template compromise, and adversarial interference while maintaining high recognition accuracy and system scalability. By harmonizing these emerging paradigms, this work establishes a unified vision of trustworthy digital identity, combining the precision of biometrics, the decentralization of blockchain, the clarity of XAI, and the resilience of quantum computation. It lays a scientific and technological foundation for the next generation of secure, ethical, and transparent au- thentication systems.