The world's leading ISO/IEC 30107-3 Compliant Passive Facial Liveness

Liveness detection is critical to when using face biometrics for digital onboarding and authentication, as well as unattended physical access. ID R&D’s IDLive® Face is the world’s first truly passive facial liveness detection technology to identify spoofing attacks with NO user participation – no blinking, head turning, moving the phone back and forth, video recordings, etc. It works invisibly in the background, making it fast and completely frictionless for the user while preventing fraudsters from knowing when it’s happening.

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All the Security. None of the Friction.

The goal of face biometrics in authentication is to improve security and the user experience. Relying on something you are, your face, is more secure than traditional methods that use something you know or something have, but no method is immune to spoofing attempts. Liveness detection is critical to ensuring the integrity of biometric security and only passive liveness works without introducing friction back into the process.

ID R&D Passive Facial Liveness is Level 1 and Level 2 ISO 30107-3 compliant, having passed iBeta Presentation Attack Detection testing with perfect scores. While this isn’t unique, achieving compliance with a passive solution is rare. Why? Because it’s not easy to deliver a liveness check that is fast, frictionless and also accurate. Our competitors offer active solutions that confuse and frustrate users — leading to abandonment.

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How it Works

ID R&D relies on a single image capture for analysis. Our technology uses the SAME selfie image for liveness AND face matching. ID R&D is the only company to pass iBeta Level 2 Presentation Attack Detection Compliance with a passive, single image approach.

- Requires no additional software on the capture side.
Works for both iOS and Android devices
Generates no incremental traffic to the server, making it ideal for customers operating in countries where bandwidth is scarce or expensive.
Eliminates the vulnerability that occurs when liveness detection is separate from the action to capture the selfie for face recognition.
Determines liveness in under a second.
Enables easy integration because the product is deployed as a separate independent function, requiring no changes to the user interface or communication interfaces.