Liveness Detection
Techniques used to verify that an input (e.g., biometric) originates from a live subject rather than a spoof or replay, enhancing system security and integrity.
Definition
Anti-spoofing measures—challenge-response protocols, motion analysis, texture analysis, or multi-modal checks—that distinguish genuine biometric inputs (face, voice) from photos, videos, or recordings. Governance requires regular liveness-test updates to counter evolving spoofing attacks, integration into authentication pipelines, and logging of failed attempts for security monitoring and compliance reporting.
Real-World Example
A banking app’s face-login adds a liveness check: it prompts users to blink or turn their head, verifying real-time motion before unlocking. All liveness-check failures are logged and reviewed weekly by security analysts to detect new spoofing tactics and refine detection algorithms.
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