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Non-Uniform Attacks Against Pseudoentropy

机译:针对伪熵的非均匀攻击

摘要

De, Trevisan and Tulsiani [CRYPTO 2010] show that every distribution over n-bit strings which has constant statistical distance to uniform (e.g., the output of a pseudorandom generator mapping n-1 to n bit strings), can be distinguished from the uniform distribution with advantage epsilon by a circuit of size O( 2^n epsilon^2).We generalize this result, showing that a distribution which has less than k bits of min-entropy, can be distinguished from any distribution with k bits of delta-smooth min-entropy with advantage epsilon by a circuit of size O(2^k epsilon^2/delta^2). As a special case, this implies that any distribution with support at most 2^k (e.g., the output of a pseudoentropy generator mapping k to n bit strings) can be distinguished from any given distribution with min-entropy k+1 with advantage epsilon by a circuit of size O(2^k epsilon^2).Our result thus shows that pseudoentropy distributions face basically the same non-uniform attacks as pseudorandom distributions.
机译:De,Trevisan和Tulsiani [CRYPTO 2010]表明,在n位字符串上的每个分布具有统一的统计距离(例如,将n-1映射到n位字符串的伪随机生成器的输出),可以与该均值区分开。通过大小为O(2 ^ n epsilon ^ 2)的电路获得具有优势epsilon的分布。我们对该结果进行了概括,表明可以将具有小于k位的最小熵的分布与具有k位的delta的任何分布区分开来通过大小为O(2 ^ k epsilon ^ 2 / delta ^ 2)的电路获得具有优势epsilon的最小光滑熵。作为一种特殊情况,这意味着可以将最多支持2 ^ k的任何分布(例如,将k映射到n个位串的伪熵生成器的输出)与具有熵eps的最小熵k + 1的任何给定分布区分开。通过一个大小为O(2 ^ k epsilon ^ 2)的电路,我们的结果因此表明伪熵分布面临与伪随机分布基本相同的非均匀攻击。

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