NeuroCrypt: Entropy-Constrained Neural Key Generation via Contrastive Learning and Fuzzy Extraction From Biometrics

In the evolving field of biometric cryptography, generating high-entropy cryptographic keys directly from noisy physiological signals remains a challenging task. This paper proposes NeuroCrypt, a novel framework for robust and entropy-constrained neural key generation that integrates supervised cont...

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Detaylı Bibliyografya
Yayımlandı:IEEE Access
Asıl Yazarlar: Harshit Sharma, Simran Kaur
Materyal Türü: Makale
Baskı/Yayın Bilgisi: IEEE 2025-01-01
Konular:
Biometric cryptography
Neural key generation
Fuzzy extractor
Entropy maximization
Contrastive learning
Privacy-preserving AI
Online Erişim:https://ieeexplore.ieee.org/document/11224375/
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https://ieeexplore.ieee.org/document/11224375/

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