3D Facial Authentication via Social Profile Cross-Verification
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Solution Overview
Problem
Conventional authentication systems using facial recognition are not robust enough to prevent data vulnerability, as they can be hacked by fake users using images of real users, leading to unauthorized access to personal information.
Innovation Solution
A computer-implemented method and system that authenticates users by receiving an image or video, identifying facial descriptors, comparing them to previously captured images, and cross-verifying with social networking profiles to generate notifications about authorized access, incorporating features like facial recognition, color histograms, and 3D rendering to enhance security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional facial recognition is used for authentication, then the authentication process is simple and fast, but the system is vulnerable to hacking by fake users using images of real users
Solution Approach 1:
The patent transitions from 2D image-based facial recognition to 3D depth mapping for facial authentication. By capturing the three-dimensional geometry of the face using depth sensors and comparing it against stored 3D facial models, the system creates a new dimensional layer of verification that prevents spoofing with flat images while maintaining computational feasibility through efficient 3D point cloud matching algorithms
Solution Approach 2:
The system performs preliminary actions by capturing and storing multiple 3D facial scans of authorized users during the enrollment phase, creating a comprehensive 3D facial model database. This pre-prepared 3D reference data enables rapid comparison and verification during authentication without requiring complex real-time processing, thus enhancing security while keeping the authentication process efficient
2Reliability
If multiple verification methods are implemented to improve security, then data vulnerability is reduced, but the authentication process becomes more complex
Solution Approach 1:
The system performs self-service by automatically capturing depth maps, extracting 3D facial features, comparing them against stored models, and making authentication decisions without requiring user intervention beyond presenting their face. The multi-layered verification process including 3D geometry matching, liveness detection, and cross-profile verification operates autonomously, maintaining ease of operation while significantly enhancing authentication robustness
Data Source
AI summary
Systems and methods for authenticating a user, the method including receiving an image of a user of a device, identifying a first facial descriptor of the user from the received image and from previously captured images of the user, and determining a difference between the first facial descriptor from the received image and that from the previously captured images. The method further includes identifying a second facial descriptor of a non-user from the previously captured images of the user, and applying facial recognition to images stored in a plurality of second social networking profiles associated with a first social networking profile of the user to identify the second facial descriptor from the images stored in the second social networking profiles. Based on the difference and the second facial descriptor, the user may be authenticated.