Passive Liveness Detection

Prevent injection attacks and detect deepfakes with Keyless' advanced passive liveness detection. Combined with MFA, it makes large-scale attacks nearly impossible.

Passive Liveness Detection

Prevent injection attacks and detect deepfakes with Keyless' advanced passive liveness detection. Combined with MFA, it makes large-scale attacks nearly impossible.

What is Liveness?

Liveness detection ensures a biometric sample is from a real person, preventing fraud attacks using photos or deepfakes. There are two types:

Active liveness requires user actions, like blinking or nodding.

Passive liveness analyzes natural traits, like texture and reflections, without user actions.

Deepfakes can now mimic active liveness, so passive liveness is now preferred for accurately identifying synthetic identity attacks.

Detecting Deepfakes with Keyless

Keyless uses passive liveness detection to verify the authenticator's identity. While our full list of indicators is confidential, here are common traits detected by passive liveness technologies.

Colors

Detecting skin tone variations and anomalies in synthetic images.

Patterns

Analyzing background patterns like moiré effects on screens.

Reflections

Identifying light reflections on eyes and skin to confirm authenticity.

Periocular Region

Observing micro-movements around the eyes that deepfakes struggle to replicate.

Vein Recognition

Using vein patterns to enhance identity verification accuracy.

Vibration

Detecting micro-vibrations from holding a phone for added security.

Movement Detection

Distinguishing live individuals from still images or objects.