# Browsing by Subject "Extractor"

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Item Distributed computing and cryptography with general weak random sources(2011-08) Li, Xin, Ph. D.; Zuckerman, David I.; Alvisi, Lorenzo; Kalai, Yael; Klivans, Adam; Waters, BrentShow more The use of randomness in computer science is ubiquitous. Randomized protocols have turned out to be much more efficient than their deterministic counterparts. In addition, many problems in distributed computing and cryptography are impossible to solve without randomness. However, these applications typically require uniform random bits, while in practice almost all natural random phenomena are biased. Moreover, even originally uniform random bits can be damaged if an adversary learns some partial information about these bits. In this thesis, we study how to run randomized protocols in distributed computing and cryptography with imperfect randomness. We use the most general model for imperfect randomness where the weak random source is only required to have a certain amount of min-entropy. One important tool here is the randomness extractor. A randomness extractor is a function that takes as input one or more weak random sources, and outputs a distribution that is close to uniform in statistical distance. Randomness extractors are interesting in their own right and are closely related to many other problems in computer science. Giving efficient constructions of randomness extractors with optimal parameters is one of the major open problems in the area of pseudorandomness. We construct network extractor protocols that extract private random bits for parties in a communication network, assuming that they each start with an independent weak random source, and some parties are corrupted by an adversary who sees all communications in the network. These protocols imply fault-tolerant distributed computing protocols and secure multi-party computation protocols where only imperfect randomness is available. The probabilistic method shows that there exists an extractor for two independent sources with logarithmic min-entropy, while known constructions are far from achieving these parameters. In this thesis we construct extractors for two independent sources with any linear min-entropy, based on a computational assumption. We also construct the best known extractors for three independent sources and affine sources. Finally we study the problem of privacy amplification. In this model, two parties share a private weak random source and they wish to agree on a private uniform random string through communications in a channel controlled by an adversary, who has unlimited computational power and can change the messages in arbitrary ways. All previous results assume that the two parties have local uniform random bits. We show that this problem can be solved even if the two parties only have local weak random sources. We also improve previous results in various aspects by constructing the first explicit non-malleable extractor and giving protocols based on this extractor.Show more Item Explicit two-source extractors and more(2016-05) Chattopadhyay, Eshan; Zuckerman, David I.; Gal, Anna; Li, Xin; Waters, BrentShow more In this thesis we study the problem of extracting almost truly random bits from imperfect sources of randomness. This is motivated by the wide use of randomness in computer science, and the fact that most accessible sources of randomness generate correlated bits, and at best contain some amount of entropy. We follow Chor and Goldreich [CG88] and Zuckerman [Z90], and model weak sources using min-entropy, where an (n,k)-source X is a distribution on n bits and takes any string x with probability at most 2^-k. It is known that it is impossible to extract random bits from a single (n,k)-source, and Chor and Goldreich [CG88] raised the question of extracting randomness from two such independent (n,k)-sources. Existentially, such 2-source randomness extractors exist for min-entropy k >=log n + O(1), but the best known construction prior to work in this thesis requires min-entropy k >=0.499 n [B2]. One of the main contributions of this thesis is an explicit 2-source extractor for min-entropy log^C n, for some constant C. Other results in this thesis include improved ways of extracting random bits from various other sources of randomness, as well as stronger notions of randomness extraction. Our results have applications in privacy amplification [BBR88,Mau92,BBCM95], which is a classical problem in information cryptography, and give protocols that achieve almost optimal parameters. Other applications include explicit constructions of non-malleable codes, which is a relaxation of the notion of error-detection codes and have applications in tamper-resilient cryptography [DPW10].Show more