Amazon Rekognition launches Face Liveness to deter fraud in facial verification

Today, AWS announced the general availability of Amazon Rekognition Face Liveness, a new feature to deter fraud in facial verification. Face Liveness helps customers detect in seconds that real users, and not bad actors using spoofs, are accessing their services. Financial services, gig economy, telco, healthcare, social media, and other customers use facial verification during online onboarding, step-up authentication, and age-based access restriction. These customers need to deter bad actors that use spoofs for unauthorized access. Face Liveness analyzes a short user selfie video to detect whether the user is real or a spoof. Face Liveness detects spoofs presented to the camera (e.g. printed photos, digital photos or videos, or 3D masks) and spoofs that bypass the camera (e.g. pre-recorded real or deepfake videos). Face Liveness returns a high-quality selfie frame for downstream [Amazon Rekognition Face Matching](https://docs.aws.amazon.com/rekognition/latest/dg/faces-comparefaces.html) or [Age Estimation](https://docs.aws.amazon.com/rekognition/latest/dg/faces.html) analysis. Customers can easily add Face Liveness to their React web, native iOS, and native Android applications using open-source AWS Amplify SDKs. Face Liveness automatically scales up or down based on demand and customers pay only for the face liveness checks performed. No infrastructure management, hardware-specific implementation, or machine learning (ML) expertise is required. Face Liveness uses ML models trained on diverse datasets to support high accuracy across user skin tones, ancestries, and devices. Face Liveness is available in US East (N. Virginia), US West (Oregon), Europe (Ireland), and Asia Pacific (Tokyo, Mumbai). To learn more, visit [feature overview](https://aws.amazon.com/rekognition/face-liveness/), [blog](https://aws.amazon.com/blogs/machine-learning/detect-real-and-live-users-and-deter-bad-actors-using-amazon-rekognition-face-liveness/), [documentation](https://docs.aws.amazon.com/rekognition/latest/dg/face-liveness.html), and [pricing](https://aws.amazon.com/rekognition/pricing/) webpages.