IDLive™ Face

The world's first passive facial liveness detection

Stop Face Biometrics Spoofing

The use of facial recognition for authentication is becoming increasingly prevalent — especially on mobile devices. But between easy access to images on social media and advances in digital and print image resolution, biometric systems have security gaps that fraudsters can exploit to successfully spoof a facial recognition system.

In order for face biometrics to truly gain mainstream adoption as a better mode of authentication, it is essential to determine whether the presented face is genuine or an attempt to spoof the system by presenting an artificial representation of it. Thus, automated detection of presentation attacks and specifically liveness detection, has become a necessary component of any authentication system that is based on face biometrics for verification.

What is Facial Liveness Detection?

Facial liveness has emerged as a way to stop fraud and ensure the integrity of face biometrics as a means of authentication. Whereas face recognition for authentication can accurately answer the question “Is this the right person?” it doesn’t answer the question, “Is this a real person?”. This is the role of liveness detection.

Facial liveness detection works with a biometric system to measure and analyze physical characteristics and reactions in order to determine if a biometric sample is being captured from a living subject who is present at the point of capture.

Understanding passive vs. active facial liveness is crucial. Most of today’s facial liveness technologies are “active”, requiring users to blink, turning their heads or move their phone back and forth. This results in three issues: First, fraudsters can present a photo with cut out with eye holes, use a mask or show a video to trick the system. Second, challenge-response techniques put attackers on alert that they are being checked. And lastly, active methods create friction that slows the authentication process, increases abandon rates and diminishes the overall user experience.

Passive Facial Liveness Detection is Critical!

IDLive Face is the world’s first truly passive facial liveness detection SDK that identifies spoofing attempts with NO user participation. Equally important is the fact that the liveness detection occurs in the background, making it completely frictionless for the user while preventing fraudsters from knowing when it’s happening.

Users authorize camera access for applications that use IDLive Face. After that, the liveness detection SDK works passively with mobile, web and IoT interfaces.

IDLive Face is Levels 1 and 2 ISO/IEC 30107-3 PAD compliant and with a perfect score. Read more here.

IDLive Face Features

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    Passive UX – no action required
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    No special capture software required 
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    Single image analysis (vs multiple frames or video) determines liveness in under a second
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    Background implicit method of attack detection
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    Identification of natural face movements (when available)
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    Level 1 and 2 ISO 30107-3 compliance; tested with both iOS and Android 
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    Cross channel input: mobile, web, stand-alone devices

IDLive Face Benefits

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    Strengthen the security of mobile and web authentication
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    Eliminate friction by working in the background with no active participation from the user
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    Prevents fraudsters from knowing liveness detection is occurring
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    Ease remote customer onboarding and improve identity proofing processes
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    Reduce fraudulent accounts and account takeovers
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    Generates no incremental traffic to the server, making it ideal for customers operating in countries where bandwidth is scarce or expensive
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    Eases integration because the product is deployed as a separate independent function, requiring no changes to the user interface or communication interfaces

Use Cases

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Mobile and online face biometric authentication
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Remote customer onboarding
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Biometric-based device login
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Physical biometric access systems

Passive Liveness Explained

See how passive facial liveness works

Read our Whitepaper

Facial Liveness Whitepaper

How to Reduce Friction and Fraud in Digital Onboarding with Passive Facial Liveness.

Face Recognition is frequently used to match the image on a user’s government issued ID to a selfie. Liveness detection is equally crucial to ensure fraudsters cannot use high resolution print outs, masks or video to spoof the process. This paper dives deeper into the technology, including passive vs active approaches and considerations for choosing the right solution for your use case. Read it here.

Don't deploy face recognition for authentication without passive facial liveness! IDLive Face is delivered as a liveness detection SDK or Docker image that can be integrated with any face recognition software to prevent spoofing attacks. Contact us to learn more.