Biometric Verification via Machine-Readable Optical Labels

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Solution Overview

Problem

Current biometric verification methods face challenges in ensuring secure and private authentication, particularly in online transactions, as they often require remote server connections and storage of sensitive biometric data, which can lead to security risks and privacy concerns.

Innovation Solution

A biometric verification method using machine-readable optical labels, such as QR codes, that encodes biometric data into a machine-readable format, allowing for on-site authentication without remote server connections, with the ability to revoke credentials quickly and securely, and integrating additional security checks through meta-characteristics evaluation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If biometric data is stored on remote servers for verification, then authentication can be performed remotely, but security risks and privacy concerns increase due to potential data breaches

Engineering Contradiction:
Improveremote authentication capabilityVSAvoidsecurity and privacy protection
Core Design Contradiction:
Ease of operationVSReliability

Solution Approach 1:

The patent extracts the biometric verification capability from remote servers and embeds it locally in the credential itself through machine-readable optical labels containing biometric templates. This allows the credential to be self-verifying without requiring connection to external servers, thus maintaining remote authentication capability while eliminating security risks associated with centralized biometric data storage

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent introduces machine-readable optical labels as an intermediary that carries encoded biometric templates. These labels serve as a portable, self-contained verification mechanism that mediates between the credential holder and the verification system, eliminating the need for direct server connections while maintaining security and privacy

Inventive Principle:
Principle #24Intermediary (Mediator)

2Reliability

If traditional biometric verification systems are used, then authentication can be performed, but system complexity and cost increase due to required server infrastructure and secure storage mechanisms

Engineering Contradiction:
Improveauthentication functionalityVSAvoidserver infrastructure requirements
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent creates a copy of the biometric verification capability by encoding the biometric template directly into the machine-readable optical label. This copy allows verification to be performed locally without requiring the original server infrastructure, thus maintaining authentication functionality while dramatically reducing system complexity and cost

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The patent uses machine-readable optical labels that can be printed at low cost and replaced if compromised. These disposable or short-living credentials eliminate the need for expensive, complex server infrastructure while maintaining reliable authentication functionality through their self-contained biometric templates

Inventive Principle:
Principle #27Cheap short-living objects (Disposable)

Data Source

PatentUS10990776B2Methods and devices for biometric verification
Publication Date: 2021.04.27 VERIDAS DIGITAL AUTHENTICATION SOLUTIONS SL
  • US10990776B2 patent drawing
  • US10990776B2 patent drawing
  • US10990776B2 patent drawing

AI summary

Methods and devices for biometric verification are disclosed. During registration or encoding, a first vector representing biometric features of a subject is generated. Machine-readable optical labels based on the first vector are then generated. During validation or decoding, physical characteristics representative of the subject are captured, the physical characteristic containing biometric features of the subject. The biometric features are identified in the captured physical characteristics. A second vector representing the identified biometric features is generated. The machine-readable optical label is read to decode the first vector. The first vector is compared with the second vector to compute a match probability.