Biometric Identification Systems With Noisy Enrollment for Gaussian Source
Information Theory
2021-09-01 v1 Cryptography and Security
math.IT
Abstract
In the present paper, we investigate the fundamental trade-off of identification, secrecy, storage, and privacy-leakage rates in biometric identification systems for hidden or remote Gaussian sources. We introduce a technique for deriving the capacity region of these rates by converting the system to one where the data flow is in one-way direction. Also, we provide numerical calculations of three different examples for the generated-secret model. The numerical results imply that it seems hard to achieve both high secrecy and small privacy-leakage rates simultaneously. In addition, as special cases, the characterization coincides with several known results in previous studies.
Cite
@article{arxiv.2010.10799,
title = {Biometric Identification Systems With Noisy Enrollment for Gaussian Source},
author = {Vamoua Yachongka and Hideki Yagi and Yasutada Oohama},
journal= {arXiv preprint arXiv:2010.10799},
year = {2021}
}