We study how to extract randomness from a C-interleaved source, that is, a source comprised of C independent sources whose bits or symbols are interleaved. We describe a simple approach for constructing such extractors that yields: • For some δ > 0, c > 0, explicit extractors for 2-interleaved sources on {0, 1} when one source has min-entropy at least (1 − δ)n and the other has min-entropy at l...

A deterministic extractor for an elliptic curve is a function that converts a random point on the curve to a random-looking bit-string, which is statistically close to a uniformly random bit-string. The problem of converting random points of an elliptic curve into random bits has several cryptographic applications. In this talk, we propose two simple and efficient deterministic extractors for a...

Fuzzy extractors (Dodis et al., Eurocrypt 2004) convert repeated noisy readings of a high-entropy secret into the same uniformly distributed key. A minimum condition for the security of the key is the hardness of guessing a value that is similar to the secret, because the fuzzy extractor converts such a guess to the key. We define fuzzy min-entropy to quantify this property of a noisy source of...

Protecting our environment and natural resources is a major global challenge. “Protectors” (law enforcement agencies) try to protect these natural resources, while “extractors” (criminals) seek to exploit them. In many domains, such as illegal fishing, the extractors know more about the distribution and richness of the resources than the protectors, making it extremely difficult for the protect...

We propose two simple and efficient deterministic extractors for J(Fq), the Jacobian of a genus 2 hyperelliptic curve H defined over Fq, for some odd q. Our first extractor, SEJ, called sum extractor, for a given point D on J(Fq), outputs the sum of abscissas of rational points on H in the support of D, considering D as a reduced divisor. Similarly the second extractor, PEJ, called product extr...

We present a general method to reduce the error of any extractor. Our method works particularly well in the case that the original extractor extracts up to a constant fraction of the source min-entropy and achieves a polynomially small error. In that case, we are able to reduce the error to (almost) any ε, using only O(log(1/ε)) additional truly random bits (while keeping the other parameters o...

We deal with the problem of storing a set of K elements that are taken from a large universe of size N , such that membership in the set can be determined with high probability by looking at just one bit of the representation. Buhrman et al. show an explicit construction with about K2 logN storing bits. We show an explicit construction with about K1+o(1) storing bits, that gets closer to the op...

We present a general method to reduce the error of any extractor. Our method works particularly well in the case that the original extractor extracts up to a constant fraction of the source min-entropy and achieves a polynomially small error. In that case, we are able to reduce the error to (almost) any ", using only O(log(1=")) additional truly random bits (while keeping the other parameters o...