Biometric Key Generation via Distinguishable Feature Transform
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Solution Overview
Problem
Existing biometrics-based cryptographic key generation systems fail to effectively tolerate biometric feature diversities across different dimensions and do not adequately utilize the varying distinguishabilities of biometric features, leading to security concerns and limited key space expansion.
Innovation Solution
A biometrics-based cryptographic key generation system that employs a user-dependent distinguishable feature transform unit to transform N-dimensional biometric features into M-dimensional feature signals, using cascaded linear discriminant analysis or generalized symmetric max minimal distance criteria, and a stable key generation unit that generates cryptographic keys based on bit information proportional to the degree of distinguishability in each dimension, defined by statistical characteristics of authentic and global feature signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If biometric features are directly transformed into cryptographic keys without dimensionality reduction, then the key space is larger, but the computational complexity and storage requirements increase
Solution Approach 1:
The patent segments the biometric feature space into multiple dimensions, where each dimension corresponds to a specific biometric attribute (e.g., ridge count, pore position, minutiae points). This segmentation allows the system to process and utilize each dimension independently, reducing the overall computational complexity while maintaining the total key space derived from all dimensions combined.
Solution Approach 2:
The patent transforms the original biometric feature space into a new dimensional representation through mathematical transformations (such as Principal Component Analysis or other dimensionality reduction techniques). This dimensionality change reduces the number of features while preserving the essential discriminatory information, thereby reducing system complexity without significantly compromising key space.
2Adaptability or versatility
If error correction codes are added to tolerate biometric variations, then the tolerance to biometric diversities is improved, but the key length and processing overhead increase
Solution Approach 1:
The patent performs preliminary characterization of biometric feature diversities during the enrollment phase. By analyzing and pre-processing the biometric data to understand its variability patterns, the system can establish tolerance thresholds and transformation parameters in advance, avoiding the need for complex real-time error correction during authentication and reducing processing overhead.
Solution Approach 2:
The patent dynamically adjusts transformation parameters and tolerance thresholds based on the observed biometric diversity characteristics. By changing parameters such as dimensionality reduction factors, threshold values, and weighting coefficients according to the specific biometric modality and user characteristics, the system achieves adaptive tolerance without requiring fixed complex error correction codes.
3Ease of manufacture
If all biometric dimensions are treated equally in key generation, then the process is simpler, but the distinguishability of different biometric features is not optimized
Solution Approach 1:
The patent applies local quality by assigning different weights, transformations, or processing methods to different biometric dimensions based on their individual distinguishability characteristics. High-distinguishability dimensions (such as fingerprint minutiae) receive more emphasis or higher-weighted transformations, while lower-distinguishability dimensions receive相应 adjustments, optimizing the overall key generation precision without requiring complex manual configuration.
Data Source
AI summary
The present invention provides a biometrics-based cryptographic key generation system and method. A user-dependent distinguishable feature transform unit provides a feature transformation for each authentic user, which receives N-dimensional biometric features and performs a feature transformation to produce M-dimensional feature signals, such that the transformed feature signals of the authentic user are compact in the transformed feature space while those of other users presumed as imposters are either diverse or far away from those of the authentic user. A stable key generation unit receives the transformed feature signals to produce a cryptographic key based on bit information respectively provided by the M-dimensional feature signals, wherein the length of the bit information provided by the feature signal of each dimension is proportional to the degree of distinguishability in the dimension.