熵平坦化的紧下界

Yi-Hsiu Chen, Mika Göös, S. Vadhan, Jiapeng Zhang
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引用次数: 7

摘要

我们研究熵平坦化:给定电路残雪隐式地描述一个n位X来源(即X是残雪的输出在一个统一的随机输入),构造另一个电路CY描述源,(1)源Y近平(统一的支持),和(2)Y的夏侬熵单调相关X标准的解决方案是完全CY评估CXΘ(n2)次独立输入和连接结果(遵循渐近均分财产的正确性)。在本文中,我们证明了这在黑盒结构中是最优的:任何用于熵平坦化的电路CY,重复查询CX作为oracle需要ω(n2)次查询。熵平坦化是用于从单向函数构造伪随机生成器和其他密码原语的组件[12,22,13,6,11,10,7,24]。它也用于统计零知识完备问题之间的约简[19,23,4,25]。Θ(n2)查询复杂度通常是主要的效率瓶颈。我们的下界可以被看作是证明Vadhan和Zheng (STOC 2012)目前从任意单向函数构造伪随机生成器的最佳方法具有最佳效率的一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Tight Lower Bound for Entropy Flattening
We study entropy flattening: Given a circuit CX implicitly describing an n-bit source X (namely, X is the output of CX on a uniform random input), construct another circuit CY describing a source Y such that (1) source Y is nearly flat (uniform on its support), and (2) the Shannon entropy of Y is monotonically related to that of X. The standard solution is to have CY evaluate CX altogether Θ(n2) times on independent inputs and concatenate the results (correctness follows from the asymptotic equipartition property). In this paper, we show that this is optimal among black-box constructions: Any circuit CY for entropy flattening that repeatedly queries CX as an oracle requires ω(n2) queries. Entropy flattening is a component used in the constructions of pseudorandom generators and other cryptographic primitives from one-way functions [12, 22, 13, 6, 11, 10, 7, 24]. It is also used in reductions between problems complete for statistical zero-knowledge [19, 23, 4, 25]. The Θ(n2) query complexity is often the main efficiency bottleneck. Our lower bound can be viewed as a step towards proving that the current best construction of pseudorandom generator from arbitrary one-way functions by Vadhan and Zheng (STOC 2012) has optimal efficiency.
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