Biometric template protection

Overview

A stored biometric template (iris, face, fingerprint, signature) should be protected so that it cannot be turned back into the biometric and cannot be linked to another template of the same person enrolled elsewhere with a different key 2311.04633 §1. The standard covering this asks for unlinkability but gives no quantitative way to measure it 2311.04633 §1. Earlier analyses were binary curve comparisons, assumed uniform data, or covered one scheme type 2311.04633 §2.

The core idea of the measure: given comparison scores for mated pairs (same person, different keys) and non-mated pairs (different people, different keys), turn the ratio of their densities into a per-score value, then average it over the mated distribution 2311.04633 §3 2311.04633 §4. The shared invariant is that a value of 0 means no score favours "same person" and a value of 1 means the mated and non-mated distributions do not overlap 2311.04633 §4.2.

Card: General Framework to Evaluate Unlinkability in Biometric Template Protection Systems.

Variants

The paper does not propose a protection scheme. It measures four schemes, each with one linkage function, and the variants below are those measured 2311.04633 §6.1. The same card covers all of them.

Iris XOR with random strings

Iris codes from Log-Gabor features, combined with random strings by XOR, scored with the paper's PIC score 2311.04633 §6.1. Reported D_sys = 0, because the distributions fully overlap 2311.04633 §6.2 2311.04633 fig. 4. Card: General Framework to Evaluate Unlinkability in Biometric Template Protection Systems.

Signature with homomorphic encryption

On-line signature global features (40 of 100) protected with homomorphic encryption, compared by Euclidean distance 2311.04633 §6.1. Reported D_sys = 0 under the PIC score 2311.04633 §6.2. The encryption parameters are not stated in the paper 2311.04633 §6.1. Card: General Framework to Evaluate Unlinkability in Biometric Template Protection Systems.

Face with Bloom filters

LGBPHS face features protected by a Bloom filter. Three linkage functions are reported: the PIC score gives D_sys = 0.07 2311.04633 §6.2. Reconstruct then Hamming distance gives 0.25. Hamming weight difference gives 0.07, and permutation with XOR gives 0.06 2311.04633 §6.3 2311.04633 fig. 5. The maximum over these functions is 0.25 2311.04633 §6.3. Bloom filter size and hashing are not stated 2311.04633 §6.1. Card: General Framework to Evaluate Unlinkability in Biometric Template Protection Systems.

Fingervein with block re-mapping

Maximum-curvature vein extraction, block re-mapping, and rotated cross-correlation on the UTFVP data (60 subjects, 2 sessions) 2311.04633 §6.1. Reported D_sys = 0.92 2311.04633 §6.5. Block size is not stated 2311.04633 §6.1. Card: General Framework to Evaluate Unlinkability in Biometric Template Protection Systems.

When to use which

The paper's evaluation protocol is one fixed setting. Choose the parts that vary by the constraints you have.

Implementation sketch

The steps follow the paper's evaluation protocol 2311.04633 §5. The formulas are from 2311.04633 §4. Write your own estimator for the densities. The paper does not fix a bin count or bandwidth.

# Inputs: mated scores (different keys, same person),
#         non-mated scores (different people, different keys), omega
# Estimate p(s | H_m) and p(s | H_nm) on one shared score grid [§5]
# Likelihood ratio  LR(s) = p(s | H_m) / p(s | H_nm)  [eq. 4]
# Prior-scaled odds  x(s) = omega * LR(s)  [eq. 6]
# Local measure: D(s) = 0 if x <= 1, else 2x / (1 + x) - 1  [eq. 13]
# If p(s | H_nm) is zero, the limit is D(s) = 1  [eq. 13] [§6.3]
# Global measure: D_sys = integral of p(s | H_m) * D(s) ds, over p(H_m)
#                                                              [eqs. 16-18]

Notes on the sketch:

• Use mated pairs enrolled with different keys. The paper's non-mated pairing is one sample against the first sample of other subjects. Report that choice 2311.04633 §5 2311.04633 §6.1.
• Empty tails in the non-mated distribution set D(s) = 1 by rule. With finite samples, this can come from sampling alone, not only from true unlinkability 2311.04633 §6.3.
• Scores below a certain value can favour mated pairs and still give a small D_sys, because they carry little probability mass. The paper's face example has such scores with p(s | H_m) < 0.005 2311.04633 §6.2.

Contradictions

• Fingervein. DET-based analyses report that the system is unlinkable, with EER rising from 1.91 % to 4.48 %. This measure gives D_sys = 0.92 2311.04633 §6.5 2311.04633 fig. 7. The paper does not resolve the disagreement, and only the authors' own readings of the earlier analyses are given.
• Face, Hamming weight difference. The table-level result is 0.07, but the text says the value rises to 0.08 2311.04633 §6.3 2311.04633 fig. 5. Both are reported; the source of the difference is not stated.

Papers

• General Framework to Evaluate Unlinkability in Biometric Template Protection Systems: defines the score-wise D(s) and system-wide D_sys unlinkability measures and applies them to iris XOR, signature HE, face Bloom filters and fingervein block re-mapping.