# Identification, Secrecy, Template, and Privacy-Leakage of Biometric Identification System Under Noisy Enrollment

## TL;DR

This paper analyzes the fundamental trade-offs among identification, secrecy, template, and privacy-leakage rates in biometric identification systems with noisy enrollment channels, introducing a novel capacity region characterization.

## Contribution

It introduces a new capacity region characterization for biometric systems with noisy enrollment, using a novel technique with two auxiliary random variables, extending prior noiseless models.

## Key findings

- Capacity region characterized for noisy enrollment channels
- Reduction to previous models in special cases
- Novel technique with two auxiliary variables

## Abstract

In this study, we investigate fundamental trade-off among identification, secrecy, template, and privacy-leakage rates in biometric identification systems. Ignatenko and Willems (2015) studied this system assuming that the channel in the enrollment process of the system is noiseless and they did not consider the template rate. In the enrollment process, however, it is highly considered that noise occurs when bio-data is scanned. In this paper, we impose a noisy channel in the enrollment process and characterize the capacity region of the rate tuples. The capacity region is proved by a novel technique via two auxiliary random variables, which has never been seen in previous studies. As special cases, the obtained result shows that the characterization reduces to the one given by Ignatenko and Willems (2015) where the enrollment channel is noiseless and there is no constraint on the template rate, and it also coincides with the result derived by G\"unl\"u and Kramer (2018) where there is only one individual.