Face Liveness Detection
Facical Liveness Detection is the ultimate solution to stay safe against deepfake and spoofing attacks. Ensure customer safety and authenticate only genuine users.
Preventing Fraud
Traditional facial anti spoofing systems can be tricked using photographs, videos, or even hyper-realistic masks. Liveness detection ensures that only a live human can pass through the system, significantly reducing the likelihood of fraudulent access.
Enhancing Security
For industries that handle sensitive information or high-value transactions, such as finance and healthcare, liveness detection provides an essential additional layer of security, safeguarding systems against unauthorized access.
Building Trust
With the proliferation of digital services, customers expect robust security measures to protect their identities and personal data. Liveness detection helps build trust by ensuring that only legitimate users can access services.
Compliance with Regulations
Many industries are subject to strict regulatory requirements, such as Know Your Customer (KYC) and Anti-Money Laundering (AML) rules. Facial liveness detection helps organizations meet these regulations.
3D Face Liveness Detection Solution
3D Face Liveness Detection
Outstanding Characteristics
Facial Liveness Detection Empowering businesses globally to verify individuals!
3D Face Liveness Detection
3D Passive Facial Anti Spoofing SDK
We provides a comprehensive solution for face recognition that incorporates 3D Passive Facial Anti Spoofing SDK.
Try in Action
Please select face liveness detection tab for face liveness detection testing
Mobile Face Liveness Detection SDK
We have developed a face liveness detection API using our SDK.
iOS & Android compatible liveness detection SDKs and complete API integration.
Effective Facial Anti Spoofing Mechanism Against Spoofing Attacks
Detect Various Attacks
MiniAI Web Facial Anti Spoofing aims to generate the same trust and user experience as face-to-face interaction. As a result, a series of liveness verification mechanisms for anti-spoofing were developed and the essence is to make sure submitted recordings were indeed taken from a live person in front of the camera.
The latest mechanism for Presentation Attack Detection (PAD) prevents forgery through replay attacks like videos, recorded deepfakes, or avatars. It is based on texture detection and AI.
Enhancing Security
By means of texture analysis, the texture of a recaptured image, a video, a projection, or other fake attempts is now detected for reliable biometric anti-spoofing. Today, PAD detects even remote-controlled 3D avatars, deepfakes, as well as 3D masks. MiniAI has earned another patent for its liveness detection technology.
It is based on an optical flow algorithm to discern between a 2D and a 3D object. By means of a simple but sensitive motion trigger, the algorithm captures images automatically, preventing an attacker from presenting or swapping different photos.
Questions About Face Liveness Detection SDK
Face Anti Spoofing is the process of ensuring that the system is accessed by a live/real individual only. It prevents spoofing attempts i.e. someone trying to access the system with a face mask, photo or a deep fake video.
Basic Anti Spoofing systems without active & passive capabilities often fail to detect real individuals in complex environments such as low lighting, reflections, and poor camera settings. Only advanced liveness detection systems ensure 100% accuracy and spoof prevention ensuring that only live individuals are able to access the system.
3D liveness is an advanced form of biometric authentication, a technology that verifies your identity using unique physical characteristics. Unlike traditional methods that use 2D images (like a flat photograph), 3D liveness creates a three-dimensional map of your face which ensures you’re not an imposter.
Anti-Spoofing Presentation Attack Detection in liveness checks is a security feature that identifies and prevents attempts to trick biometric systems using false representations, such as photos, videos, masks, or other artificial artifacts. It’s essential for maintaining the integrity and reliability of biometric authentication systems.
Primary function of liveness detection in biometrics is to distinguish between a live person and a synthetic or non-live representation. This is crucial for securing biometric systems against unauthorized access or fraudulent activities, ensuring that the biometric data being captured is from a live, present individual.