Amazon Rekognition Face Liveness Detects Real Users, Deters Fraud

Amazon Web Services (AWS) has introduced Amazon Rekognition Face Liveness, a new feature designed to enhance the security of facial recognition systems. The tool aims to help businesses ascertain whether an individual logging into an online service is a real, live person or if a fraudster is attempting to use images or videos for unauthorized access.

This service is targeted towards sectors such as financial services, healthcare, and telecommunications that rely on facial recognition for user verification. Previously, distinguishing a live person from advanced spoofing techniques, like 3D masks or video injection, posed a challenge. AWS notes that traditional methods, such as gesture detection, have proven costly to maintain and insufficient against sophisticated attacks.

Amazon Rekognition Face Liveness seeks to address these issues by providing a more reliable method for confirming user presence. The feature integrates into existing facial recognition workflows, including identity verification via selfies or age estimation. The objective is to reduce fraud and associated costs for businesses.

According to AWS, the Face Liveness feature can be readily integrated into web and mobile applications. Businesses can employ it for processes like online onboarding, step-up authentication, and bot detection, where confirming genuine and live users is critical.