首页> 外文会议>International Conference on the Theory and Application of Cryptology and Information Security >Basing PRFs on Constant-Query Weak PRFs: Minimizing Assumptions for Efficient Symmetric Cryptography
【24h】

Basing PRFs on Constant-Query Weak PRFs: Minimizing Assumptions for Efficient Symmetric Cryptography

机译:基于恒定查询弱PRF的PRF:最小化高效对称密码学的假设

获取原文

摘要

Although it is well known that all basic private-key cryptographic primitives can be built from one-way functions, finding weak assumptions from which practical implementations of such primitives exist remains a challenging task. Towards this goal, this paper introduces the notion of a constant-query weak PRF, a function with a secret key which is computationally indistinguishable from a truly random function when evaluated at a constant number s of known random inputs, where s can be as small as two. We provide iterated constructions of (arbitrary-input-length) PRFs from constant-query weak PRFs that even improve the efficiency of previous constructions based on the stronger assumption of a weak PRF (where polynomially many evaluations are allowed). One of our constructions directly provides a new mode of operation using a constant-query weak PRF for IND-CPA symmetric encryption which is essentially as efficient as conventional PRF-based counter-mode encryption. Furthermore, our constructions yield efficient modes of operation for keying hash functions (such as MD5 and SHA-1) to obtain iterated PRFs (and hence MACs) which rely solely on the assumption that the underlying compression function is a constant-query weak PRF, which is the weakest assumption ever considered in this context.
机译:虽然众所周知,所有基本的私钥加密基元可以由单向函数构建,找到这种基元的实际实现的弱假设仍然是一个具有挑战性的任务。朝着这个目标,介绍了恒定查询弱PRF的概念,一个函数与秘密密钥的函数从已知随机输入的常数S评估时从真正随机函数计算地无法区分,其中s可以是小的作为两个。我们提供常见查询弱PRF的(任意输入长度)PRF的迭代结构,即甚至根据弱PRF的较强假设(其中允许多项评估),甚至提高先前结构的效率。我们的一个结构直接提供了使用恒定查询弱PRF的新操作模式,用于IND-CPA对称加密,基本上与传统的基于PRF的反作模式加密一样有效。此外,我们的结构产生了有效的操作模式,用于键控散列函数(如MD5和SHA-1),以获得迭代的PRF(和因此MAC),该PRFS(和因此MAC)仅依赖于底层压缩函数是恒定查询弱PRF的假设,这是在这种背景下曾经考虑过的最薄弱的假设。

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