Biometric Identification Systems with Noisy Enrollment for Gaussian Sources and Channels

Abstract

In the present paper, we investigate the fundamental trade-off of identification, secret-key, storage, and privacy-leakage rates in biometric identification systems for remote or hidden Gaussian sources. We use a technique of converting the system to one where the data flow is in one-way direction to derive the capacity region of these rates. Also, we provide numerical calculations of three different examples for the system. The numerical results imply that it seems hard to achieve both high secret-key and small privacy-leakage rates simultaneously.

Keywords

• biometric identification system
• noisy enrollment
• privacy-leakage
• entropy power inequality