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Lightweight Two-Factor-Based User Authentication Protocol for IoT-Enabled Healthcare Ecosystem in Quantum Computing.

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ISNR-PQC: isometry noise resilience post quantum cryptography primitive.

Alawi A Al-Saggaf1,2, Muhamad A Felemban3,4

  • 1Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia. alawi@kfupm.edu.sa.

Scientific Reports
|June 29, 2026
PubMed
Summary

This study introduces ISNR-PQC, a novel post-quantum cryptographic primitive designed for noisy data like biometrics. It offers enhanced security against quantum adversaries by leveraging lattice-based cryptography and an isometry noise resilience approach.

Keywords:
Biometric AuthenticationBiometric Template ProtectionLearning with Errors (LWE)Noise-Resilient CryptographyPost-Quantum CryptographySimilarity-Preserving Encryption

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Area of Science:

  • Cryptography and Information Security
  • Biometrics and Pattern Recognition
  • Post-Quantum Cryptography

Background:

  • Practical security systems often use noisy data (biometrics, sensors, PUFs), challenging cryptographic primitive development.
  • Existing solutions (fuzzy schemes, fuzzy vaults) use error-correcting codes (ECCs) but risk information leakage.
  • The need for robust cryptographic methods resilient to inherent data variability and quantum threats is critical.

Purpose of the Study:

  • To construct ISNR-PQC, an Isometry Noise Resilient Post-Quantum Cryptographic primitive for naturally noisy data sources.
  • To apply ISNR-PQC to secure biometric data authentication.
  • To provide security guarantees against quantum adversaries using lattice-based cryptography.

Main Methods:

  • Construction of ISNR-PQC based on lattice-based cryptography and NIST standard FIPS 203.
  • Formalization of correctness, robustness, and [Formula: see text]-restricted IND-CPA indistinguishability within a unified security model.
  • Utilizing an isometry-based threshold mapping to measure closeness of ancillary data to original encrypting data for noise resilience.

Main Results:

  • ISNR-PQC demonstrates noise resilience by accepting ancillary data close to original encrypting data.
  • The primitive provides security against quantum adversaries under the Learning with Errors (LWE) assumption.
  • Formal security proofs establish correctness, robustness, and indistinguishability.

Conclusions:

  • ISNR-PQC effectively addresses a significant challenge in biometric authentication theory.
  • The proposed primitive offers a promising foundation for future biometric and noisy-data security systems.
  • ISNR-PQC provides a secure and noise-resilient solution leveraging post-quantum cryptography.