Secure hamming distance based biometric authentication

Abstract

Concerns of privacy, template security and efficiency of biometric authentication systems have received considerable research attention in the recent past. Binary template representations have been shown to provide significant improvements in efficiency without compromising accuracy for a variety of biometric modalities including fingerprints, palmprints and iris. Most of the secure authentication protocols work with generic feature representations or propose new secure templates for specific modalities. In this work, we propose an authentication protocol that works with any binary biometric representation that employs hamming distance for comparison and convert it into a secure, privacy preserving protocol that provides template protection. We also provide the ability to use masks while computing the hamming distance. The protocol retains the accuracy of the underlying representation as demonstrated by our experiments.

Security and efficiency analysis of the Hamming distance computation protocol based on oblivious transfer

“…Kulkarni et al propose a biometric authentication scheme based on iris matching. Their scheme uses the somewhat homomorphic encryption scheme of Boneh et al .…”

“…We now apply the proposed attack as a practical example on biometric authentication systems with full success. Note that the matching procedure for fingerprint, palm print, or iris actually measures the Hamming distance between the two bit‐strings X and Y that encode the biometric sample and template (e.g., ).…”

THRIVE: threshold homomorphic encryption based secure and privacy preserving biometric verification system

“…There are also some works on secure Hamming distance calculation by using cryptographic primitives [64,[66][67][68]. These papers, however, limit the scope of their works only to secure Hamming distance calculation.…”

“…Kulkarni et al [64] propose a biometric authentication system based on somewhat homomorphic encryption scheme of Boneh et al [65], which allows an arbitrary number of addition of ciphertexts, but supports only one multiplication operation between the ciphertexts. Although the values stored on the enrollment server are the XORed values of the biometric template vector with the corresponding user's key, the user first extracts and sends her biometric features to the trusted enrollment server.…”

“…Kulkarni et al 's system [64] requires 58 s at the server side, 10 ms at the user side, and 400 Kbit bandwidth usage for authentication of single user with 2048-bit binary feature vector at 3.2 GHz. Our proposed system requires 6146 ms at the server side, 2051 ms at the user side, and 6296 Kbit bandwidth usage for the same authentication setup.…”