Identification with encrypted biometric data

Biometrics make human identification possible with a sample of a bio-metric trait and an associated database. Classical identification tech-niques lead to privacy concerns. This paper introduces a new method toidentify someone using his biometrics in an encrypted way.Our construction combines Bloom Filters with Storage and Locality-Sensitive Hashing. We apply this error-tolerant scheme, in a Hammingspace, to achieve biometric identification in an efficient way. This is thefirst non-trivial identification scheme dealing with fuzziness and encrypteddata.