Computational Robust (Fuzzy) Extractors for CRS-dependent Sources with Minimal Min-entropy
Computational Robust (Fuzzy) Extractors for CRS-dependent Sources with Minimal Min-entropy
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DOI：
10.1007/978-3-030-90453-1_24
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Hanwen Feng;Qiang Tang
中科院分区：
文献类型：
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作者：
Hanwen Feng;Qiang Tang
鲁棒（模糊）提取器非常有用，例如，来自共享弱秘密的认证密钥交换和针对活跃对手的远程生物特征认证。它们使双方能够用一个“助手”字符串提取相同的均匀随机性。更重要的是，它们有一个内置的身份验证机制，可以检测到对“helper”字符串的篡改。不幸的是，如Dodis和Wichs所示，在信息论环境中，一个鲁棒的提取器（n，k）-源需要，这与随机性提取器形成鲜明对比，只需要。现有的工作要么依赖于随机预言机，要么引入CRS，并且只适用于CRS独立的源（即使在计算环境中）。我们表明，在信息论的设置，相同的熵下界持有，即使在CRS模型，然后我们表明，我们可以有强大的提取器在计算设置为一般CRS相关的源，只有最小熵。我们进一步扩展我们的建设强大的模糊提取器。沿着的方式，我们提出了一个新的原语称为MAC，这是不可伪造的弱密钥和隐藏的所有部分信息的关键（都对辅助输入），它可能是独立的利益。
Robust (fuzzy) extractors are very useful for, e.g., authenticated key exchange from a shared weak secret and remote biometric authentication against active adversaries. They enable two parties to extract the same uniform randomness with a “helper” string. More importantly, they have an authentication mechanism built in that tampering of the “helper” string will be detected. Unfortunately, as shown by Dodis and Wichs, in the information-theoretic setting, a robust extractor for an (n,k)-source requires, which is in sharp contrast with randomness extractors which only require. Existing works either rely on random oracles or introduce CRS and work only for CRS-independent sources (even in the computational setting).In this work, we give a systematic study about robust (fuzzy) extractors for general CRSdependentsources. We show in the information-theoretic setting, the same entropy lower bound holds even in the CRS model; we then show wecanhave robust extractors in the computational setting for general CRS-dependent source that is only with minimal entropy. We further extend our construction to robust fuzzy extractors. Along the way, we propose a new primitive called-MAC, which is unforgeable with a weak key and hides all partial information about the key (both against auxiliary input); it may be of independent interests.