What is Liveness Detection?

Liveness detection is the ability of a biometric verification system to determine whether a fingerprint, face or other body part was captured by a real person or a fake (like a 3D mask or a gelatin finger). It’s also known as anti-spoofing technology. Liveness detection is a crucial capability when performing remote identity proofing and authentication. In the past, fraudsters would use photographs, masks or even resin 3D printed facial sculptures to pass themselves off as a real human and access sensitive data and devices. These are called “presentation attacks.” Fraudsters have evolved to create such sophisticated presentations that even the most advanced and accurate biometric systems may fall victim to them.

The best way to combat presentation attacks is with a certified liveness detection solution. This technology uses artificial intelligence and deep learning to evaluate the contents of a captured biometric image. It then compares the data with a stored template to determine whether it was produced by a real or spoofed body part. This method is much less susceptible to spoofing techniques and offers a more user friendly experience for end users when performing remote customer onboarding.

There are two types of liveness detection technologies: active and passive. Active liveness detection solutions require the end user to perform key movements, such as moving their head left and right or blinking in front of a camera in order to prove they are alive. While these solutions are effective, they can create an unfriendly user experience and result in onboarding abandonment. Passive liveness detection, on the other hand, doesn’t require the user to do anything. It evaluates the content of a captured biometric image and analyzes shadows, colors, audio artifacts and textures through AI algorithms.

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