Identification with Encrypted Biometric Data

Abstract

Biometrics make human identification possible with a sample of a biometric trait and an associated database. Classical identification techniques lead to privacy concerns. This paper introduces a new method to identify 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 Hamming space, to achieve biometric identification in an efficient way. This is the first non-trivial identification scheme dealing with fuzziness and encrypted data.

An extended abstract -- entitled "Error-Tolerant Searchable Encryption" -- of this work has been accepted to and will be presented at the Communication and Information Systems Security Symposium, International Conference on Communications (ICC) 2009, June 14-18, Germany. This paper is the full version. Submitted for publication