Structured Light Face Verification for Deepfake Video Calls
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Solution Overview
Problem
Current video conferencing systems fail to continuously verify the identity of users during a call, allowing attackers to inject fake media streams, which undermines security and integrity.
Innovation Solution
Implement a system with a structured irradiation projector that generates a pseudo-random dot pattern, capturing a depth map of the user's face for continuous biometric verification, ensuring genuine real-time media streams by comparing with stored biometric data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current video conferencing systems use only password and biometric data verification at login, then user authentication is simple and quick, but security is compromised allowing fake media stream injection during calls
Solution Approach 1:
The system performs preliminary biometric verification at login and then continuously performs micro-challenge verification throughout the video call. This preliminary action establishes baseline security while the continuous micro-challenges prevent fake media injection without requiring complete system redesign
Solution Approach 2:
The verification process is segmented into discrete micro-challenges (e.g., blink detection, head rotation detection) that are independently verified throughout the call. This segmentation allows complex security verification to be broken into simple, manageable checks that maintain security without overwhelming system complexity
2Reliability
If continuous biometric verification using structured light and depth mapping is implemented, then deepfake detection capability is enhanced, but processing time and computational resources increase
Solution Approach 1:
Instead of performing full biometric analysis continuously, the system performs partial verification through micro-challenges that require only specific facial actions (blink, head rotation). This partial action provides sufficient deepfake detection capability while significantly reducing processing time and computational overhead compared to continuous full biometric mapping
Solution Approach 2:
The system implements periodic micro-challenges at intervals during the video call rather than continuous verification. This periodic action maintains deepfake detection effectiveness while allowing normal video communication to proceed uninterrupted, minimizing perceived processing time and maintaining user experience
3Object-affected harmful factors
If standard security measures like user authentication and media encryption are used, then basic security is provided, but vulnerabilities remain at intermediary components where fake media can be introduced
Solution Approach 1:
The system incorporates continuous feedback loops where biometric verification results directly control media stream transmission. If verification fails or depth map analysis detects inconsistencies, the system immediately blocks the media stream. This feedback mechanism closes the security loop, preventing fake media injection without requiring fundamentally different system architecture
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Prevents the injection of deepfake media streams by continuously authenticating users, maintaining security and integrity throughout the video call.
Implementation Method 1
capturing a reflected pattern from the user's face using an irradiation sensor to produce a depth map of the user's face
Data Source
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AI summary
A system and method for continuous biometric verification during video calls to prevent the injection of deepfake media streams. The method involves actively illuminating the user's face with near-infrared light and projecting a pseudo-random dot pattern onto the face using a structured light projector. An infrared camera or LiDAR/ToF sensor captures the reflected pattern to create a depth map, which is compared with stored biometric data for continuous identity verification. The system ensures secure transmission of genuine real-time media streams by continuously matching the depth map and video feed with the biometric database, detecting and blocking any discrepancies. Key components include a dot pattern generator, structured light projector, infrared camera, LiDAR/ToF sensor, triangulation algorithm, biometric database, and face identification algorithm. The invention enhances security in digital communication platforms by providing robust protection against fraudulent activities during video calls.