SecureID-HE: Homomorphic Encryption for Privacy-Preserving Digital Identity Verification
Keywords:
Privacy-Preserving, Digital Identity, Homomorphic Encryption, Encrypted Verification, Multi-Modal Authentication, Secure Computation, Biometric Security.Abstract
Preserving privacy in digital identity verification is increasingly critical as multi-institution systemsexchange sensitive biometric and behavioral data. Traditional verification approaches typically requiredecryption during computation, exposing raw templates to potential breaches and undermining trust in large-scale deployments. This research introduces SecureID-HE, a homomorphic encryption
References
Anand, D. and V. Khemchandani, “Identity and access management systems,” in Security and Privacy of Electronic Healthcare Records: Concepts, Paradigms and Solutions, 2019, p. 61.
S. K. S. Prasanna, “GeoDNN: Geometry-aware deep neural networks for cross-domain fingerprint spoof detection,” Int. J. Intell. Syst. Appl. Eng., vol. 6, no. 1, pp. 97–107, Mar. 2018.


