Facial Biometric Authentication via Secondary Source Verification
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Solution Overview
Problem
Existing user authentication systems using facial biometrics are vulnerable to identity takeover attacks, where attackers can register fraudulent biometric data, leading to unauthorized access to user accounts.
Innovation Solution
A system that validates facial biometric data from a primary image against secondary image sources, such as social media, by comparing facial feature data to determine if the primary image matches the user associated with the account, and requests additional authentication if the comparison is ambiguous or fails to meet a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If facial biometric authentication is implemented, then user authentication capability is improved, but vulnerability to identity takeover attacks increases
Solution Approach 1:
The system performs preliminary verification by comparing the submitted facial biometric data against secondary source images before completing the registration. This advance check prevents fraudulent biometric data from being stored, thereby blocking identity takeover attacks before they can compromise user accounts.
Solution Approach 2:
The system introduces secondary source images as an intermediary verification layer between the submitted biometric data and the authentication system. These intermediary images from independent sources serve as a reference to validate whether the submitted facial data genuinely belongs to the claimed user, adding a mediating validation step that prevents attacks.
2Productivity
If facial biometric data is registered without verification, then registration speed is improved, but security against fraudulent registration deteriorates
Solution Approach 1:
The system performs preliminary verification by comparing the submitted facial biometric data against secondary source images before completing the registration. This advance check prevents fraudulent biometric data from being stored, thereby blocking identity takeover attacks before they can compromise user accounts.
3Reliability
If secondary image verification is implemented, then security against identity takeover is improved, but system complexity increases
Solution Approach 1:
The system leverages secondary sources such as social media platforms to provide their own images and verification infrastructure. Rather than building entirely new verification systems, the patent utilizes existing image repositories from these platforms, allowing the authentication system to benefit from their storage and retrieval capabilities while adding only the comparison and validation logic.
4Measurement precision
If multiple secondary images are compared, then authentication accuracy is improved, but processing time increases
Solution Approach 1:
The system compares the submitted facial biometric data against multiple secondary source images to establish a pattern of consistency. By examining multiple reference images from different times and contexts, the system builds a more robust verification process that can distinguish genuine users from attackers, with the multiple comparisons creating a statistical pattern that reveals fraud.
Data Source
AI summary
A system may receive a primary image containing a first set of facial feature data. The primary image may be sent by a facial recognition device for association with a user account. The system may also retrieve a secondary image from a secondary image source. The secondary image may contain a second set of facial feature data. The secondary image may further depict a user associated with the user account. The system may then compare the first set of facial feature data to the second set of facial feature data to determine whether the primary image depicts the user associated with the user account.