Yan Huang, Lior Malka, David Evans, and Jonathan Katz. Efficient Privacy-Preserving Biometric Identification, in 18th Network and Distributed System Security Symposium (NDSS 2011), 6-9 February 2011. [PDF, 14 pages]
We present an efficient matching protocol that can be used in many privacy-preserving biometric identification systems in the semi-honest setting. Our most general technical contribution is a new backtracking protocol that uses the by-product of evaluating a garbled circuit to enable efficient oblivious information retrieval. We also present a more efficient protocol for computing the Euclidean distances of vectors, and optimized circuits for finding the closest match between a point held by one party and a set of points held by another. We evaluate our protocols by implementing a practical privacy-preserving fingerprint matching system.
Yan Huang's talk at NDSS 2011, 9 February 2011. [PDF (2.6MB)]Poster for University of Virginia Engineering Research Symposium: [PDF (13MB)]
Library and framework for efficient, privacy-preserving biometric identification. This software package is made freely available under the MIT license.