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 G\"unl\"u 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.
翻译:基于生物鉴别学或物理识别特征的保密协议是基于生物鉴别学或物理识别特征的、有希望的验证使用小芯片的用户或装置的安全协议,最近已经对此进行了广泛研究。 Kittichokokecai和Caire(2015年)调查了使用物理识别特征的保密协议模式的最佳交换模式,在这种模式中,认证渠道的结构与监听渠道相似,来自信息理论方法。后来,G\“unl\'u”等人(2018年)扩展了该模式,在注册阶段引入了噪音,并在解密器中引入了费用限制的行动。这些研究的结果显示,在秘密钥匙、存储和隐私泄漏率等最佳比率区域的表达中,有两个辅助随机变量。然而,在这两个辅助随机变量中,计算率区域的复杂程度可能高得令人望重。由于这一问题,我们有兴趣探索认证渠道的类别,在能力区域表达离散源设置时只需要一个辅助随机变量。结果显示,在退化和不那么冷的认证渠道中,一个单一的辅助随机变量足以表达出该模型的产值区域的能力区域,作为核心存储源的存储源。此外,我们还从数据库获取了高基数据源。