【24h】

Non-Uniform Attacks Against Pseudoentropy

机译:伪熵的非均匀攻击

获取原文
           

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)的电路进行具有优势epsilon的分布。我们对这个结果进行了概括,表明具有小于k位的最小熵的分布可以通过大小为O(2 ^ k epsilon的电路)与具有优势epsil的k位的δ光滑最小熵的任何分布区分开。 ^ 2 /δ^ 2)。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。通过大小为O(2 ^ k epsilon ^ 2)的电路。因此,我们的结果表明,伪熵分布面临与伪随机分布基本相同的非均匀攻击。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号