What is Liveness Detection?

Liveness detection is a technology used in identity verification to confirm that the person submitting a biometric check, typically a selfie or video, is a real, physically present human and not a photograph, pre-recorded video, or AI-generated deepfake.

There are two main types of liveness detection. Passive liveness requires no action from the user. The system analyses a single image or short video clip using AI to detect signs of spoofing, such as reflection patterns, texture anomalies, or depth cues inconsistent with a live face. Active liveness asks the user to perform a specific action, such as blinking, turning their head, or nodding, to confirm they are present and responsive in real time.

As identity fraud has grown more sophisticated, liveness detection has become a core component of modern KYC. Deepfake technology can generate highly realistic synthetic faces and videos. Advanced liveness detection systems use AI trained specifically to identify deepfake characteristics, including unnatural skin texture, edge artefacts, and inconsistent lighting, that are invisible to the human eye.