Coding Solutions for the Secure Biometric Storage Problem
Davide Schipani, Joachim Rosenthal

TL;DR
This paper revisits the fuzzy commitment scheme for secure biometric storage, analyzing error-correcting codes and data distribution effects, and proposes solutions to practical implementation challenges.
Contribution
It provides insights into optimal error-correcting codes for biometric data and addresses real-world implementation issues of the fuzzy scheme.
Findings
Identification of suitable low-rate, large-minimum distance error-correcting codes with efficient decoding
Analysis of biometric data redundancy and its impact on scheme capacity
Proposed solutions to practical implementation challenges
Abstract
The paper studies the problem of securely storing biometric passwords, such as fingerprints and irises. With the help of coding theory Juels and Wattenberg derived in 1999 a scheme where similar input strings will be accepted as the same biometric. In the same time nothing could be learned from the stored data. They called their scheme a "fuzzy commitment scheme". In this paper we will revisit the solution of Juels and Wattenberg and we will provide answers to two important questions: What type of error-correcting codes should be used and what happens if biometric templates are not uniformly distributed, i.e. the biometric data come with redundancy. Answering the first question will lead us to the search for low-rate large-minimum distance error-correcting codes which come with efficient decoding algorithms up to the designed distance. In order to answer the second question we relate…
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Taxonomy
TopicsBiometric Identification and Security · User Authentication and Security Systems · Chaos-based Image/Signal Encryption
