Fuzzy Extractors for Asymmetric Biometric Representations

Fuzzy extractors are recently proposed error-tolerant cryptographic primitives that are potentially useful to protect biometric templates. However, there are challenges in adopting these primitives. Firstly, fuzzy extractors require the data obtained during both enrollment and verification to be in the same feature representation. However, for better performance on ROC, multiple high quality samples can be obtained during enrollment which result in an asymmetric setting whereby data obtained in enrollment and verification are stored in different representations. Secondly, fuzzy extractors only concern about the strength of the secret key extracted, and does not directly assure that privacy is preserved.