English
Related papers

Related papers: Extractors for Polynomial Sources over $\mathbb{F}…

200 papers

We consider the problem of extracting randomness from \textit{sumset sources}, a general class of weak sources introduced by Chattopadhyay and Li (STOC, 2016). An $(n,k,C)$-sumset source $\mathbf{X}$ is a distribution on $\{0,1\}^n$ of the…

Computational Complexity · Computer Science 2021-10-26 Eshan Chattopadhyay , Jyun-Jie Liao

We continue the study of constructing explicit extractors for independent general weak random sources. The ultimate goal is to give a construction that matches what is given by the probabilistic method --- an extractor for two independent…

Computational Complexity · Computer Science 2015-03-10 Xin Li

We continue a line of work on extracting random bits from weak sources that are generated by simple processes. We focus on the model of locally samplable sources, where each bit in the source depends on a small number of (hidden) uniformly…

Computational Complexity · Computer Science 2022-05-30 Omar Alrabiah , Eshan Chattopadhyay , Jesse Goodman , Xin Li , João Ribeiro

We prove that random low-degree polynomials (over $\mathbb{F}_2$) are unbiased, in an extremely general sense. That is, we show that random low-degree polynomials are good randomness extractors for a wide class of distributions. Prior to…

Computational Complexity · Computer Science 2025-04-22 Omar Alrabiah , Jesse Goodman , Jonathan Mosheiff , João Ribeiro

We construct explicit deterministic extractors for polynomial images of varieties, that is, distributions sampled by applying a low-degree polynomial map $f : \mathbb{F}_q^r \to \mathbb{F}_q^n$ to an element sampled uniformly at random from…

Computational Complexity · Computer Science 2023-01-18 Zeyu Guo , Ben Lee Volk , Akhil Jalan , David Zuckerman

A long line of work in the past two decades or so established close connections between several different pseudorandom objects and applications. These connections essentially show that an asymptotically optimal construction of one central…

Computational Complexity · Computer Science 2023-05-31 Xin Li

Randomness extractors and error correcting codes are fundamental objects in computer science. Recently, there have been several natural generalizations of these objects, in the context and study of tamper resilient cryptography. These are…

Cryptography and Security · Computer Science 2015-05-04 Eshan Chattopadhyay , Vipul Goyal , Xin Li

A $(k,\varepsilon)$-non-malleable extractor is a function ${\sf nmExt} : \{0,1\}^n \times \{0,1\}^d \to \{0,1\}$ that takes two inputs, a weak source $X \sim \{0,1\}^n$ of min-entropy $k$ and an independent uniform seed $s \in \{0,1\}^d$,…

Computational Complexity · Computer Science 2018-01-11 Tom Gur , Igor Shinkar

The known constructions of negligible error (non-malleable) two-source extractors can be broadly classified in three categories: (1) Constructions where one source has min-entropy rate about $1/2$, the other source can have small…

Information Theory · Computer Science 2023-06-13 Divesh Aggarwal , Eldon Chung , Maciej Obremski

Non-malleable extractors are generalizations and strengthening of standard randomness extractors, that are resilient to adversarial tampering. Such extractors have wide applications in cryptography and explicit construction of extractors.…

Computational Complexity · Computer Science 2024-04-29 Xin Li , Yan Zhong

In 2005 Bourgain gave the first explicit construction of a two-source extractor family with min-entropy rate less than $1/2$. His approach combined Fourier analysis with innovative but inefficient tools from arithmetic combinatorics and…

Combinatorics · Mathematics 2019-07-31 Mark Lewko

We study the problem of extracting random bits from weak sources that are sampled by algorithms with limited memory. This model of small-space sources was introduced by Kamp, Rao, Vadhan and Zuckerman (STOC'06), and falls into a line of…

Computational Complexity · Computer Science 2021-08-25 Eshan Chattopadhyay , Jesse Goodman

We propose a new model of a weakly random source that admits randomness extraction. Our model of additive sources includes such natural sources as uniform distributions on arithmetic progressions (APs), generalized arithmetic progressions…

Computational Complexity · Computer Science 2014-10-28 Abhishek Bhowmick , Ariel Gabizon , Thái Hoàng Lê , David Zuckerman

In this paper we give improved constructions of several central objects in the literature of randomness extraction and tamper-resilient cryptography. Our main results are: (1) An explicit seeded non-malleable extractor with error $\epsilon$…

Computational Complexity · Computer Science 2016-08-02 Xin Li

For $S\subseteq \mathbb{F}^n$, consider the linear space of restrictions of degree-$d$ polynomials to $S$. The Hilbert function of $S$, denoted $\mathrm{h}_S(d,\mathbb{F})$, is the dimension of this space. We obtain a tight lower bound on…

Computational Complexity · Computer Science 2024-05-17 Alexander Golovnev , Zeyu Guo , Pooya Hatami , Satyajeet Nagargoje , Chao Yan

In a recent breakthrough \cite{CZ15}, Chattopadhyay and Zuckerman gave an explicit two-source extractor for min-entropy $k \geq \log^C n$ for some large enough constant $C$. However, their extractor only outputs one bit. In this paper, we…

Computational Complexity · Computer Science 2015-08-06 Xin Li

We provide a unified method for constructing explicit distributions which are difficult for restricted models of computation to generate. Our constructions are based on a new notion of robust extractors, which are extractors that remain…

Computational Complexity · Computer Science 2026-05-11 Farzan Byramji , Daniel M. Kane , Jackson Morris , Anthony Ostuni

Dodis and Wichs introduced the notion of a non-malleable extractor to study the problem of privacy amplification with an active adversary. A non-malleable extractor is a much stronger version of a strong extractor. Previously, there are…

Cryptography and Security · Computer Science 2015-03-19 Xin Li

We study deterministic extractors for oblivious bit-fixing sources (a.k.a. resilient functions) and exposure-resilient functions with small min-entropy: of the function's n input bits, k << n bits are uniformly random and unknown to the…

Computational Complexity · Computer Science 2010-12-14 Yakir Reshef , Salil Vadhan

We identify a new notion of pseudorandomness for randomness sources, which we call the average bias. Given a distribution $Z$ over $\{0,1\}^n$, its average bias is: $b_{\text{av}}(Z) =2^{-n} \sum_{c \in \{0,1\}^n} |\mathbb{E}_{z \sim…

Computational Complexity · Computer Science 2019-05-31 Arnab Bhattacharyya , Philips George John , Suprovat Ghoshal , Raghu Meka
‹ Prev 1 2 3 10 Next ›