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IEEE Information Theory Workshop (ITW)

Secret-Key Generation with PUFs and Biometric Identifiers for Compound Authentication Channels

Vamoua Yachongka, Rémi A. Chou

Published Nov 24, 2024• 2 citations
Publisher

Abstract

In this study, we investigate the fundamental limits of secret-key generation with physical identifiers for compound authentication channels. Our contributions in this paper are the derivations of inner and outer bounds on the optimal tradeoff of secret-key, storage, and privacy-leakage rates for general discrete sources, and we show that these bounds are tight for Gaussian sources. In special cases, our characterizations reduce to existing results derived in previous works.

DOI
10.1109/itw61385.2024.10806941

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In this study, we investigate the fundamental limits of secret-key generation with physical identifiers for compound authentication channels. Our contributions in this paper are the derivations of inner and outer bounds on the optimal tradeoff of secret-key, storage, and privacy-leakage rates for general discrete sources, and we show that these bounds are tight for Gaussian sources. In special cases, our characterizations reduce to existing results derived in previous works.
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Secret-key agreement based on biometric or physical identifiers is a promising security protocol for authenticating users or devices with small chips and has been extensively studied recently. Kittichokechai and Caire (2015) investigated the optimal trade-off in a secret-key agreement model with physical identifiers, where the structure of the authentication channels is similar to the wiretap channels, from information theoretic approaches. Later, the model was extended by Günlü et al. (2018) introducing noise in the enrollment phase and cost-constrained actions at the decoder. The results of these studies show that two auxiliary random variables are involved in the expressions of the optimal rate regions of secret-key, storage, and privacy-leakage rates. However, with these two auxiliary random variables, the complexity of computing the rate region may be prohibitively high. Due to this problem, we are interested in exploring classes of authentication channels that need only one auxiliary random variable in the capacity region expression for discrete source settings. The result shows for the class of degraded and less noisy authentication channels, a single auxiliary random variable is sufficient to express the capacity region of the model. As an example, we also derive the capacity region of secret-key, storage, and privacy-leakage rates for binary sources. Furthermore, the capacity region for scalar Gaussian sources is derived under Gaussian authentication channels.
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.
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.