Biometric Hash Verification Using Error-Probability Candidate Bits
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Solution Overview
Problem
Current biometric systems face security and privacy risks due to the storage of biometric features, which can be compromised and used for unauthorized access or reveal personal information, and existing error correction methods lead to significant entropy loss and reduced system strength.
Innovation Solution
A biometric verification device that uses error probabilities to generate candidate bit strings from noisy biometric data, reducing entropy loss and enhancing security by allowing focused generation of candidate bit strings, and a biometric enrollment device that generates multiple diversified enrollment bit strings using error probabilities to minimize error correction overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If error correction coding is applied to correct biometric differences, then verification reliability is improved, but entropy loss increases and system strength deteriorates
Solution Approach 1:
The patent changes the parameter of error correction from fixed code-based correction to adaptive correction based on bit error probabilities. By adjusting the correction strategy according to the reliability of each bit position, the system achieves better verification reliability while minimizing entropy loss, as it only corrects where necessary rather than applying uniform correction across all bits
Solution Approach 2:
The patent applies partial error correction by focusing only on the most probable error positions identified through bit error probability analysis. Instead of correcting all possible errors or applying comprehensive error correction codes, the system performs selective correction on specific bits with high error probability, thereby reducing the entropy loss while maintaining sufficient verification reliability
2Reliability
If comprehensive error correction is performed, then bit error rate is reduced, but computational complexity increases
Solution Approach 1:
The patent applies local quality by treating different bit positions differently based on their error probabilities. Instead of uniform error correction across all bits, the system identifies and corrects only those bits with high error probabilities, allocating computational resources locally where they are most needed rather than applying comprehensive correction to the entire bit string
Solution Approach 2:
The patent performs partial error correction by focusing computational effort on the most likely error positions rather than executing complete error correction procedures. This selective approach reduces the computational complexity while still achieving acceptable bit error rates by correcting only the critical errors
3Loss of information
If multiple candidate bit strings are generated, then entropy loss is reduced, but the number of operations increases
Solution Approach 1:
The patent changes the approach from generating all possible candidate bit strings to generating only the most probable candidates based on bit error probability analysis. By adjusting the generation strategy according to error probabilities, the system reduces entropy loss while limiting the number of operations to only those candidates with significant probability of being correct
Solution Approach 2:
The patent performs partial candidate generation by creating only a subset of all possible candidate bit strings - specifically those that are most likely to be correct based on error probability analysis. This selective generation reduces the number of operations required while still capturing the essential candidates needed to minimize entropy loss
Data Source
AI summary
A biometric verification device (100) arranged to compare a reference hash (480) with a verification bit string (420) obtained from a biometric, the biometric verification device comprising: - a candidate bit string generator (130) arranged to generate candidate bit strings (430) from the verification bit string and error probabilities, - a hash unit (140) arranged to apply a cryptographic hash function to said generated candidate bit strings to obtain candidate hashes, - a comparison unit (160) arranged to verify if a candidate hash generated by the hash unit matches a reference hash.