Nonmalleable Digital Lockers and Robust Fuzzy Extractors in the Plain Model 📺
We give the first constructions in the plain model of 1) nonmalleable digital lockers (Canetti and Varia, TCC 2009) and 2) robust fuzzy extractors (Boyen et al., Eurocrypt 2005) that secure sources with entropy below 1/2 of their length. Constructions were previously only known for both primitives assuming random oracles or a common reference string (CRS). We define a new primitive called a nonmalleable point function obfuscation with associated data. The associated data is public but protected from all tampering. We construct a digital locker using a similar paradigm. Our construction achieves nonmalleability over the output point by placing a CRS into the associated data and using an appropriate non-interactive zero-knowledge proof. Tampering is protected against the input point over low-degree polynomials and over any tampering to the output point and associated data. Our constructions achieve virtual black box security. These constructions are then used to create robust fuzzy extractors that can support low-entropy sources in the plain model. By using the geometric structure of a syndrome secure sketch (Dodis et al., SIAM Journal on Computing 2008), the adversary's tampering function can always be expressed as a low-degree polynomial; thus, the protection provided by the constructed nonmalleable objects suffices.
Reusable Fuzzy Extractors for Low-Entropy Distributions
Fuzzy extractors (Dodis et al., in Advances in cryptology—EUROCRYPT 2014, Springer, Berlin, 2014, pp 93–110) convert repeated noisy readings of a secret into the same uniformly distributed key. To eliminate noise, they require an initial enrollment phase that takes the first noisy reading of the secret and produces a nonsecret helper string to be used in subsequent readings. Reusable fuzzy extractors (Boyen, in Proceedings of the 11th ACM conference on computer and communications security, CCS, ACM, New York, 2004, pp 82–91) remain secure even when this initial enrollment phase is repeated multiple times with noisy versions of the same secret, producing multiple helper strings (for example, when a single person’s biometric is enrolled with multiple unrelated organizations). We construct the first reusable fuzzy extractor that makes no assumptions about how multiple readings of the source are correlated. The extractor works for binary strings with Hamming noise; it achieves computational security under the existence of digital lockers (Canetti and Dakdouk, in Advances in cryptology—EUROCRYPT 2008, Springer, Berlin, 2008, pp 489–508). It is simple and tolerates near-linear error rates. Our reusable extractor is secure for source distributions of linear min-entropy rate. The construction is also secure for sources with much lower entropy rates—lower than those supported by prior (nonreusable) constructions—assuming that the distribution has some additional structure, namely, that random subsequences of the source have sufficient minentropy. Structure beyond entropy is necessary to support distributions with low entropy rates. We then explore further how different structural properties of a noisy source can be used to construct fuzzy extractors when the error rates are high, building a computationally secure and an information-theoretically secure construction for large-alphabet sources.