Active Liveness Detection Solution
Liveness Detection Solution?
Active liveness detection is a security measure used in facial recognition and other biometric systems. It aims to ensure your users are real people interacting with the system, not someone trying to bypass it with a photograph, video, mask, or a deepfake.
Unlike passive liveness detection, which runs in the background, active solutions require your users to take an action upon request. For example, the system may ask them to do a quick action, like blinking or turning your head, during verification.
Analyzing this action, the machine searches for indications of a living individual. This may entail observing how eyes move, how expressions vary, or how light bounces off users skin.
Luxand.cloud active liveness detection solution employs advanced algorithms and machine learning techniques. These algorithms can detect anomalies in behavior or inconsistencies in biometric data, further enhancing the system's ability to differentiate between genuine users and fraudulent attempts.
What facial movements may active liveness detection ask you to do?
- Eye movements
Blinking is a frequent request. The system can check for the natural closing and opening of eyelids, something a static image can't replicate.
- Looking around
You might be asked to move your head to show different angles of your face. This helps assess depth perception and movement range, which pre-recorded videos or masks often lack.
- Mouth movements
Opening and closing your mouth, or even just slightly pursing your lips, can be another prompt. This detects natural movement and validates it's not a static image.
- Subtle expressions
The system can ask you to raise your eyebrows, smile briefly, or puff out your cheeks. These subtle movements are hard to fake with a photo or pre-recorded video.
- Blowing cheeks
The system can ask you to puff out your cheeks as a way to show that you're a real person. This action changes the shape of your face in a way that's difficult to replicate with a fake image or video.
- Make a surprised face
The system can ask you to make a surprised face as a way to show that you're a real person since this action changes your facial expression in a way that's difficult to replicate it.
How It Works
A report by PXL Vision mentions conversion rate improvements of up to 67% by reducing fraudulent dropouts compared to passive solutions.
A study by Aite Group found that 72% of consumers surveyed felt more confident in the security of their accounts when biometric authentication included liveness detection. This can potentially lead to increased customer trust and loyalty.
A report by LexisNexis Risk Solutions estimates that the global cost of AML compliance is around $100 billion annually. Liveness detection can help ensure businesses meet compliance standards, potentially avoiding hefty fines.