Eliminating Leakage in Reverse Fuzzy Extractors
نویسندگان
چکیده
منابع مشابه
Fuzzy Extractors
This chapter presents a general approach for handling secret biometric data in cryptographic applications. The generality manifests itself in two ways: we attempt to minimize the assumptions we make about the data, and to present techniques that are broadly applicable wherever biometric inputs are used. Because biometric data comes from a variety of sources that are mostly outside of anyone’s c...
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We describe a method of cryptographically-secure key extraction from a noisy biometric source. The computational security of our method can be clearly argued through hardness of Learning Parity With Noise (LPN). We use a fuzzy commitment scheme so the extracted key is chosen by definition to have uniformly random bits. The biometric source is used as the noise term in the LPN problem. A key ide...
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Last time we proved the Leftover Hash Lemma, which states that if X is a random variable with universe U and H∞(X) ≥ k, ε > 0, and H is a universal hash family of size 2 with output length l = k − 2 log(1/ε), then Ext(x, h) = h(x) is a (k, ε/2) extractor with seed length d and output length m. In other words, Ext(x, h) extracts l bits from x that are ε-close to uniform, with ε = 12 √ 2−l. For a...
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Fuzzy extractors are used to generate reliably reproducible randomness from a biased, noisy source. Known constructions of fuzzy extractors are built from a strong extractor, and a secure sketch, a function that transforms a biased noisy secret value into a public value, simultaneously hiding the secret and allowing for error correction. A robust sketch is secure against adversarial modificatio...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Forensics and Security
سال: 2018
ISSN: 1556-6013,1556-6021
DOI: 10.1109/tifs.2017.2774500