Develop your liveness detection web application with our tools.
Face PAD is a sophisticated web component designed for liveness detection, a critical feature in facial recognition systems that safeguards against identity theft. This framework excels at identifying presentation attack events by verifying the presence of a real person in front of the camera rather than a spoof artifact. Uses a challenge-response authentication mechanism and advanced neural networks for detecting attacks, Face PAD ensures that only live, legitimate users can access the system, significantly enhancing the security and reliability of facial recognition technology.
Features included
Passive & Active
Combines advanced neural networks and challenge-response authentication mechanism to provide comprehensive protection against presentation attacks.
Real-Time Verification
Provides real-time verification of users, ensuring immediate detection of fraudulent attempts and maintaining the integrity of the facial recognition process.
User-Friendly Interface
Features a user-friendly interface that guides users through the process of capturing a selfie easily and securely. Ensures a smooth and efficient experience.
Session Recording
Records a video of the session in compliance with ANSSI recommendations for remote identity verification service providers (PVID).
Multi-Platform Compatibility
Compatible with Android and Apple devices, as well as any personal computer equipped with a webcam. Ensures broad accessibility and usability.
Angular & JavaScript
Compatible with both Angular and JavaScript, allowing seamless integration into various web applications.
Specifications
Tutorial.
Interactive Tutorial for Seamless Start.
The process begins with an interactive tutorial that guides users through the steps of using Face PAD. This tutorial explains the functionality of the system, detailing how the liveness detection works and what to expect during the verification process. By providing clear instructions and visual aids, the tutorial ensures that users understand each step, from capturing a selfie to completing the challenge-response authentication. This user-friendly introduction sets the stage for a smooth and efficient verification experience.
Challenge-Response.
Capturing and Analyzing Biometric Data.
Once the tutorial is complete, Face PAD captures biometric data using the device’s camera. Users are guided to take a selfie, with the system ensuring optimal conditions for image capture. The process combines both passive liveness detection, monitoring natural facial movements, and active liveness detection, which requires users to perform specific actions, such as moving their head. This dual approach helps to verify that the individual is real and not a spoof artifact, utilizing advanced neural networks to analyze the data for any signs of presentation attacks.
Analysis.
Real-Time Verification and Compliance Recording.
During the verification phase, Face PAD performs real-time analysis to confirm the user’s identity by comparing the captured biometric data with stored templates. The system also validates the digital signature of the data to ensure its authenticity and integrity. Additionally, a video of the session is recorded in compliance with ANSSI recommendations for remote identity verification service providers (PVID), providing a secure audit trail. Face PAD’s compatibility with Android and Apple devices, as well as personal computers equipped with webcams, ensures broad accessibility and usability, making it a versatile solution for various applications.
Developer documentation.
We provide comprehensive documentation and developer guides to facilitate a smooth implementation process.
