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IEEE Conference on Communications and Network Security

Privacy and secrecy with multiple measurements of physical and biometric identifiers

Onur Günlü, Gerhard G. Kramer, Maciej Skórski

Published Sep 1, 2015• 9 citations
Publisher

Abstract

Multiple measurements of a physical or biometric identifier are used at the decoder of a secrecy system to improve the secret-key vs. privacy-leakage capacity region of the single-measurement case. The capacity regions of doubly symmetric binary sources with multiple measurements are derived by applying Mrs. Gerber's lemma to mixtures of binary channels.

DOI
10.1109/cns.2015.7346815

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IEEE Transactions on Information Forensics and Security•Sep 30, 2009•176 citations
Multiple measurements of a physical or biometric identifier are used at the decoder of a secrecy system to improve the secret-key vs. privacy-leakage capacity region of the single-measurement case. The capacity regions of doubly symmetric binary sources with multiple measurements are derived by applying Mrs. Gerber's lemma to mixtures of binary channels.
The key-leakage-storage region is derived for a generalization of a classic two-terminal key agreement model. The additions to the model are that the encoder observes a hidden, or noisy, version of the identifier, and that the encoder and decoder can perform multiple measurements. To illustrate the behavior of the region, the theory is applied to binary identifiers and noise modeled via binary symmetric channels. In particular, the key-leakage-storage region is simplified by applying Mrs. Gerber's lemma twice in different directions to a Markov chain. The growth in the region as the number of measurements increases is quantified. The amount by which the privacy-leakage rate reduces for a hidden identifier as compared to a noise-free (visible) identifier at the encoder is also given. If the encoder incorrectly models the source as visible, it is shown that substantial secrecy leakage may occur and the reliability of the reconstructed key might decrease.
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.
Secret-key agreement using physical identifiers is a promising security protocol for the authentication of users and devices with small chips, owing to its lightweight security. In the previous studies, the fundamental limits of such a protocol were analyzed, and the results showed that two auxiliary random variables were involved in the capacity region expressions. However, with two auxiliary random variables, it is difficult to directly apply the expressions to derive the computable forms of the capacity regions for certain information sources such as binary and Gaussian sources, which hold importance in practical applications. In this paper, we explore the structure of authentication channels and reveal that for the classes of degraded and less noisy authentication channels, a single auxiliary random variable is sufficient to express the capacity regions. As specific examples, we use the expressions with one auxiliary random variable to derive the computable forms for binary and Gaussian sources. Numerical calculations for the Gaussian case show the trade-off between secret-key and privacy-leakage rates under a given storage rate, which illustrates how the noise in the enrollment phase affects the capacity region.
This paper addresses privacy leakage in biometric secrecy systems. Four settings are investigated. The first one is the standard Ahlswede-Csiszar secret-generation setting in which two terminals observe two correlated sequences. They form a common secret by interchanging a public message. This message should only contain a negligible amount of information about the secret, but here, in addition, we require it to leak as little information as possible about the biometric data. For this first case, the fundamental tradeoff between secret-key and privacy-leakage rates is determined. Also for the second setting, in which the secret is not generated but independently chosen, the fundamental secret-key versus privacy-leakage rate balance is found. Settings three and four focus on zero-leakage systems. Here the public message should only contain a negligible amount of information on both the secret and the biometric sequence. To achieve this, a private key is needed, which can only be observed by the terminals. For both the generated-secret and the chosen-secret model, the regions of achievable secret-key versus private-key rate pairs are determined. For all four settings, the fundamental balance is determined for both unconditional and conditional privacy leakage.