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引用次数: 2
摘要
模糊提取器从噪声源中提取稳定的密钥。它们是从生物识别来源提取密钥的基本工具。本文引入了一种新的结构,即指数中的代码偏移量。该结构是第一个可重用的模糊提取器,同时支持具有相关符号和置信度信息的结构化、低熵分布。这些特性是由最相关的应用程序(生物识别和物理不可克隆函数的关键派生)特别激发的,这些应用程序通常具有低熵和额外的统计相关性,并受益于可以利用置信度信息提高效率的提取器。指数中的码差是码差结构的一组编码(Juels and Wattenberg, CCS 1999)。线性纠错码的随机码字被用作从噪声源采样值的一次性衬垫。指数中的代码偏移量不是直接编码,而是通过对加密强组中的生成器取幂进行编码。在一般群模型中,我们引入并描述了一个直接影响结构安全性的噪声源条件。我们的条件要求源分布和代码零空间中所有向量之间的内积是不可预测的。2012 ACM主题分类安全与隐私→信息理论技术;安全和隐私→生物识别
Fuzzy extractors derive stable keys from noisy sources. They are a fundamental tool for key derivation from biometric sources. This work introduces a new construction, code offset in the exponent. This construction is the first reusable fuzzy extractor that simultaneously supports structured, low entropy distributions with correlated symbols and confidence information. These properties are specifically motivated by the most pertinent applications – key derivation from biometrics and physical unclonable functions – which typically demonstrate low entropy with additional statistical correlations and benefit from extractors that can leverage confidence information for efficiency. Code offset in the exponent is a group encoding of the code offset construction (Juels and Wattenberg, CCS 1999). A random codeword of a linear error-correcting code is used as a one-time pad for a sampled value from the noisy source. Rather than encoding this directly, code offset in the exponent encodes by exponentiation of a generator in a cryptographically strong group. We introduce and characterize a condition on noisy sources that directly translates to security of our construction in the generic group model. Our condition requires the inner product between the source distribution and all vectors in the null space of the code to be unpredictable. 2012 ACM Subject Classification Security and privacy→ Information-theoretic techniques; Security and privacy → Biometrics