Anti Deepfake

---

If an InterLink ID registered eKYC user uses an iPhone, our platform inherits TrueDepth which is an innovative camera system designed by Apple, primarily utilized for the Face ID feature on iPhones and iPads. This advanced technology leverages a combination of infrared light and sophisticated algorithms to construct a precise 3D map of the user's face, facilitating secure authentication. By projecting and analyzing thousands of invisible dots, the TrueDepth camera generates a detailed depth map while simultaneously capturing an infrared image of the face. Remarkably adaptive, TrueDepth adjusts to various alterations in appearance such as the application of makeup or changes in facial hair over time. I

Face Flashing is a revolutionary liveness detection method designed to enhance the security of facial recognition systems by employing the principles of light reflections. Our advanced protocol addresses critical vulnerabilities in existing security measures that often fall short in providing robust protection against potential attacks, particularly concerning time sensitivity. By employing a technique that randomly flashes meticulously crafted images on a screen and scrutinizing the reflected light, our Face Flashing protocol takes advantage of unique physical characteristics inherent to human faces, such as the reflection dynamics at light speed, distinct textural nuances, and irregular 3D contours. Consequently, the Face Flashing significantly raises the difficulty level for launching successful attacks on face authentication systems.

Our Video-based Liveness Detection represents a breakthrough in biometric security technology by analyzing subtle movements and characteristics within live video to confirm the authenticity of a user's face, mitigating the risks associated with spoofing attempts via photographs or recorded videos. Our system employs an advanced 3D Frictionless (passive) face liveness detection method that operates from a single image, such as a selfie, leveraging deep learning techniques for enhanced accuracy and reliability. Through our proprietary methodology, we achieve an effective 3D liveness check, coupled with capabilities for deepfake detection and identity concealment identification.

We offer a sophisticated Real-Time Attendance System that incorporates Liveness Detection and Multi-Face Recognition through an innovative Transfer Learning method. This advanced system is designed to accurately identify individuals while ensuring that they are indeed present in real-time. Our approach utilizes facial landmark detection to pinpoint key facial features, alongside the calculation of the eye aspect ratio to assess liveness, thereby mitigating the risks of spoofing attacks. By leveraging deep learning-based face embeddings, our protocol harnesses a transfer learning model that enhances recognition capability by adapting pre-trained networks.