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Related Experiment Videos

SHADOW: Secure Hidden Authenticating Digital Objects in the Wild.

Daniel Riccio

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |March 30, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces SHADOW, a new framework for secure biometric authentication. SHADOW protects user privacy by creating non-invertible and revocable biometric templates on devices, enhancing security against common threats.

    Related Experiment Videos

    Area of Science:

    • Computer Science
    • Cybersecurity
    • Biometrics

    Background:

    • Biometric authentication is widespread but lacks robust security and privacy measures.
    • Existing solutions like cancelable biometrics have limitations, including vulnerability to attacks and poor performance on edge devices.
    • Increasing pervasiveness of biometrics heightens risks of template leakage, identity theft, and cross-matching.

    Purpose of the Study:

    • To introduce SHADOW (Secure Hidden Authenticating Digital Objects in the Wild), a novel framework for secure and privacy-preserving biometric authentication.
    • To develop a system that generates non-invertible and revocable biometric representations on-device.
    • To address limitations of existing biometric protection schemes, focusing on unlinkability, renewability, and computational efficiency.

    Main Methods:

    • Developed SHADOW, a framework utilizing on-device generation of non-invertible and revocable biometric representations.
    • Employed analytically defined oscillatory functions to create a structured object binding a hidden certificate to the protected template.
    • Implemented client-aware verification via nonce-driven masking, with optional trusted hardware support.

    Main Results:

    • SHADOW achieves formal irreversibility and unlinkability by design, supporting renewability with minimal computational overhead.
    • Experiments on face, iris, and voice benchmarks show comparable recognition performance to existing methods.
    • Demonstrated robustness against inversion, bruteforce, and record multiplicity attacks.

    Conclusions:

    • SHADOW offers a secure and privacy-preserving biometric authentication solution suitable for modern embedding-based biometrics.
    • The framework's properties facilitate deployment in decentralized and edge computing environments.
    • SHADOW enhances biometric security without compromising recognition accuracy or user privacy.