Liveness Detection
Liveness detection that tells a real, present person from a photo, video replay or mask in milliseconds to stop spoofing.
Request a demo
Alfabeta liveness detection protects face-based systems from presentation attacks by confirming that a genuine, living person is in front of the camera. It analyses subtle cues such as texture, depth, micro-movement and reflection to distinguish real faces from printed photos, screen replays, cut-outs and 3D masks. As a dedicated anti-spoofing layer, it raises the security level of any verification flow by preventing the common ways an imposter tries to defeat face matching.
The technology is available in both passive and active modes. Passive liveness runs silently on a single frame or selfie, adding no friction for the user, while active mode issues a challenge-response action for higher assurance in sensitive workflows. Both modes work on ordinary RGB cameras found in phones, kiosks and access terminals, so no depth sensor or specialist hardware is required, and decisions are returned in a fraction of a second to keep authentication smooth.
Liveness detection is designed to work hand in hand with face recognition and e-KYC. By gating every identity match, it ensures that only a live, present user is ever verified or enrolled, which improves the overall accuracy and trustworthiness of the surrounding facial recognition technology. For customer-facing services this translates directly into safer, spoof-proof onboarding that increases user trust and loyalty during selfie verification.
Because it is delivered as a simple API, liveness drops into web, mobile and kiosk applications with minimal integration effort, and it complements Alfabeta products such as the payment authentication system and the e-KYC flow. Pricing follows an adjustable tiered model based on monthly API call volume, so you pay in line with real usage. The result is a practical defence against presentation attacks that hardens digital identity without slowing legitimate users down.
Presentation Attack Defence
Blocks photo, video replay, cut-out and 3D mask spoofing before a face is accepted as genuine, raising the security level of any verification flow.
Passive And Active Modes
Choose silent, single-frame passive liveness for speed or challenge-response actions for higher assurance. The same engine covers both low-friction and high-security use cases.
No Special Hardware
Works with ordinary RGB cameras on phones, kiosks and access terminals, with no depth sensor required. That keeps rollout cheap and lets you use devices your users already own.
Millisecond Decisions
Returns a real-or-fake verdict in a fraction of a second to keep authentication frictionless. Fast decisions mean liveness fits smoothly into login and onboarding journeys.
Pairs With Face Recognition
Gates every identity match so only live, present users are ever verified or enrolled. This improves the overall accuracy and trust of your face recognition technology.
Simple API Integration
Drop liveness into web, mobile and kiosk apps through clean, well-documented endpoints. It slots alongside e-KYC and payment authentication with minimal engineering effort.
Frequently asked questions
What kinds of spoofing attacks does liveness detection stop?
It defends against the main presentation attack types: printed or on-screen photos, video replays, paper cut-outs and 3D masks. By analysing texture, depth cues, micro-movement and reflection, it separates a genuine live face from these artefacts before any identity match is trusted.
What is the difference between passive and active liveness?
Passive liveness runs silently on a single frame or selfie, so the user does nothing extra and the flow stays fast. Active liveness adds a challenge-response action, such as a prompted movement, for higher assurance in sensitive workflows. You can choose the mode per use case to balance friction and security.
Does it need special cameras or depth sensors?
No. Liveness detection works with the ordinary RGB cameras already built into smartphones, kiosks and access terminals, so there is no need for infrared or depth hardware. This keeps deployment low-cost and lets customers verify on devices they already own.
How does it integrate with our verification flow?
It is delivered as a simple API that you call from web, mobile or kiosk applications, typically as a gate in front of face recognition or e-KYC. It also pairs with Alfabeta's face recognition and payment authentication products so you can build a complete, spoof-proof identity flow.
How is liveness detection priced?
Pricing uses an adjustable tiered model based on your monthly API call volume, so what you pay tracks real usage rather than a fixed licence. Our team helps you pick a starting tier and adjusts it as your verification volume changes.