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On linear-size pseudorandom generators and hardcore functions

机译:关于线性大小的伪随机数生成器和硬核函数

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摘要

We consider the question of constructing pseudorandom generators that simultaneously have linear circuit complexity (in the output length), exponential security (in the seed length), and a large stretch (linear or polynomial in the seed length). We refer to such a pseudorandom generator as an asymptotically optimal PRG. We present a simple construction of an asymptotically optimal PRG from any one-way function f : {0, 1}~n → {0, 1}~n which satisfies the following requirements: 1. f can be computed by linear-size circuits; 2. f is 2~(βn)-hard to invert, for some constant β > 0; 3. f either has high entropy, in the sense that the min-entropy of f(x) on a random input x is at least γn where β/3 + γ > 1, or alternatively it is regular in the sense that the preimage size of every output of f is fixed. Known constructions of PRGs from one-way functions can do without the entropy or regularity requirements, but they achieve slightly sub-exponential security (Vadhan and Zheng (2012) [27]). Our construction relies on a technical result about hardcore functions that may be of independent interest. We obtain a family of hardcore functions H = {h: {0, 1}~n → {0, 1}~(αn)} that can be computed by linear-size circuits for any 2~(βn)-hard one-way function f: {0, 1}~n → {0, 1}~n where β > 3α. Our construction of asymptotically optimal PRGs uses such hardcore functions, which are obtained via linear-size computable affine hash functions (Ishai et al. (2008) [24]).
机译:我们考虑构造伪随机发生器的问题,该伪随机发生器同时具有线性电路复杂度(在输出长度上),指数安全性(在种子长度上)和较大的拉伸范围(在种子长度上为线性或多项式)。我们将这种伪随机生成器称为渐近最优PRG。我们从任意一个单向函数f给出一个渐近最优PRG的简单构造:{0,1}〜n→{0,1}〜n满足以下要求:1. f可以由线性电路计算; 2. f为2〜(βn)-难以求逆,对于一定的常数β> 0; 3. f要么具有较高的熵,就某种意义而言,在随机输入x上f(x)的最小熵至少为γn,其中β/ 3 +γ> 1,或者在正像的意义上它是规则的f的每个输出的大小是固定的。单向函数的PRG的已知构造可以满足熵或规则性要求,但它们只能实现次指数级的安全性(Vadhan和Zheng(2012)[27])。我们的构建依赖于可能具有独立利益的有关硬核功能的技术成果。我们获得了一系列硬核函数H = {h:{0,1}〜n→{0,1}〜(αn)},这些函数可以通过线性大小电路针对任何2〜(βn)-hard one-路径函数f:{0,1}〜n→{0,1}〜n,其中β>3α。我们的渐近最优PRGs的构造使用这样的硬核函数,这些函数是通过线性大小的可计算仿射哈希函数获得的(Ishai等人(2008)[24])。

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