Biometric Data Management System Using Primary Data Copying

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Solution Overview

Problem

Traditional biometric identification systems face challenges in managing biometric data securely and efficiently, particularly in updating embeddings and handling unauthorized access, which leads to user annoyance, increased costs, and compromised security.

Innovation Solution

The system employs techniques to manage biometric data by storing primary data instead of input data, allowing translation of primary data without re-enrollment, generating new embeddings from primary data, and combining these methods to improve security and resilience.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional biometric systems store input data and update embeddings, then identification accuracy is maintained, but security is compromised and user annoyance increases due to re-enrollment requirements

Engineering Contradiction:
ImprovesecurityVSAvoiduser convenience
Core Design Contradiction:
ReliabilityVSEase of operation

Solution Approach 1:

The system stores a copy of the biometric input data (e.g., image) as primary data instead of storing processed embeddings. This copy can be repeatedly processed to generate new embeddings without requiring re-enrollment, maintaining both security through data freshness and user convenience through seamless operation.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The system performs preliminary processing by storing the raw input data and pre-computing multiple embeddings from it. When updates are needed, new embeddings are generated from the stored primary data without requiring users to re-provide biometric input, thus maintaining convenience while enabling security updates.

Inventive Principle:
Principle #10Preliminary action

2Reliability

If biometric data is updated by re-processing, then security is improved, but compute resources and time are consumed

Engineering Contradiction:
ImprovesecurityVSAvoidcompute resources
Core Design Contradiction:
ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system performs the computationally intensive task of processing biometric data only once during enrollment and stores the result as primary data. Subsequent security updates leverage this pre-processed data, avoiding repeated expensive processing and reducing overall compute resource consumption while maintaining security through periodic re-processing.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system changes the storage parameter from storing processed embeddings to storing raw input data. This parameter change allows the same primary data to be used with different processing algorithms and embedding versions, enabling security updates without re-collecting biometric data and reducing compute requirements.

Inventive Principle:
Principle #35Parameter changes

3Reliability

If embeddings are stored instead of input data, then data privacy is improved, but the ability to update without re-enrollment is lost

Engineering Contradiction:
Improvedata privacyVSAvoidupdate flexibility
Core Design Contradiction:
ReliabilityVSAdaptability or versatility

Solution Approach 1:

The system stores a copy of the raw input data (primary data) rather than processed embeddings. This copy serves as the foundation for generating multiple different embeddings over time, enabling both privacy protection through controlled processing and update flexibility through repeated derivation of new embeddings from the same primary data.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The system segments the biometric data management into two distinct components: primary data storage (raw input) and derived embeddings (processed representations). This segmentation allows the primary data to remain private while enabling flexible generation of updated embeddings for security maintenance without re-enrollment.

Inventive Principle:
Principle #1Segmentation

4Reliability

If re-enrollment is required for updates, then security is maintained, but user annoyance increases and productivity decreases

Engineering Contradiction:
ImprovesecurityVSAvoidoperational efficiency
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The system enables self-service updates where the stored primary data automatically serves as the basis for generating new embeddings. Users do not need to re-enroll or re-provide biometric data, and the system maintains security through automated re-processing of the stored primary data, thus improving operational efficiency while maintaining security.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system performs preliminary processing by storing raw biometric data and pre-computing embeddings during initial enrollment. When security updates are needed, the system leverages this pre-stored primary data to generate new embeddings without requiring users to repeat the enrollment process, thus maintaining productivity while ensuring security.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentUS12271456B1System to manage biometric data
Publication Date: 2025.04.08 AMAZON TECH INC
  • US12271456B1 patent drawing
  • US12271456B1 patent drawing
  • US12271456B1 patent drawing

AI summary

Maintaining the security of biometric data is an utmost priority. Biometric data is secured using one or more techniques. With one technique, biometric input such as images of a user's palm is used to generate first primary data (PD). The original biometric input is deleted from temporary secure storage while the first PD is securely stored. The first PD may then be processed later to determine a second PD. The first PD may then be deleted, and the second PD subsequently used. With another technique, biometric input or a PD may be processed by a first model to determine first secondary data (SD) that is representative of features of a particular user within a first embedding space. Later the PD may be processed by a second model to determine a second SD in a second embedding space. The first SD is deleted, and the second SD subsequently used.