In the system that we investigate here, two terminals observe the enrollment and identification biometric sequences of different individuals. The first terminal binds a secret key to each enrolled individual and stores the corresponding helper data in a public database. These helper data, on one hand, facilitate reliable determination of the individual''s identity for the second terminal, and, on the other hand, reliable reconstruction of the secret key of this individual, based on the presented biometric identification sequence. All helper data in the database are assumed to be public. Since the secret keys are used by the individuals e.g. to encrypt data, the helper data should provide no information on these secret keys. In this paper we determine what identification and secret-key rates can be jointly realized by such a biometric identification and key-binding system. We focus on the binary symmetric case and show that there exist linear codes yielding optimal performance. The setting that we investigate here is closely related to the study of the biometric identification capacity [O''Sullivan and Schmid, 2002, Willems et al., 2003] and the common randomness generation problem [Ahlswede and Csiszár, 1993]. The linear-coding part generalizes the fuzzy commitment scheme [Juels and Wattenberg, 1999].
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机译：在我们这里研究的系统中，两个终端观察了不同个体的注册和识别生物识别序列。第一终端将密钥绑定到每个注册个人，并将相应的帮助者数据存储在公共数据库中。这些助手数据一方面有助于可靠地确定个人在第二终端的身份，另一方面，根据提供的生物识别序列，可以可靠地重建该个人的秘密密钥。假定数据库中的所有辅助数据都是公开的。由于秘密密钥是由个人使用的，例如为了加密数据，帮助程序数据不应在这些秘密密钥上提供任何信息。在本文中，我们确定通过这种生物识别和密钥绑定系统可以共同实现哪些识别率和秘密密钥率。我们关注二进制对称情况，并证明存在产生最佳性能的线性代码。我们在这里研究的设置与生物特征识别能力的研究[O''Sullivan and Schmid，2002; Willems et al。，2003]和常见的随机性产生问题[Ahlswede andCsiszár，1993]密切相关。线性编码部分概括了模糊承诺方案[Juels and Wattenberg，1999]。
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