优化和实施费施林变换,实现 UC 安全零知识

Yi-Hsiu Chen, Yehuda Lindell
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引用次数: 1

摘要

Fischlin 变换(CRYPTO 2005)是 Fiat-Shamir 变换的替代方案,它可以在证明知识时进行直线提取。在这项工作中,我们将重点关注使用 Fischlin 变换从西格玛协议中构建 UC 安全零知识的问题,因为 UC 安全性--保证一般并发组合下的安全性--需要直线(非缠绕)模拟器。我们提供了一种略微简化的转换,更易于理解,并提出了算法和实现方面的优化方案,显著改善了运行时间。在实践中使用 Fischlin 的主要障碍似乎是其计算成本和实施复杂性(需要选择多个参数)。我们为选择参数提供了明确的指导和简单的方法,并表明经过我们的优化,运行时间远远低于预期。仅以 2023 MacBook 为例,使用 Fischlin 证明离散对数知识的成本仅为 0.41ms(单核)。在同一台机器上,这比普通的 Fiat-Shamir 慢了 15 倍,这是一个很大的倍数,但客观上在许多应用中并不重要。我们还扩展了转换,使其可以应用于批量证明,并展示了这样做如何比单独证明每个语句更高效。我们希望本文能鼓励并帮助实践者在相关情况下实施菲施林变换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing and Implementing Fischlin's Transform for UC-Secure Zero-Knowledge
Fischlin's transform (CRYPTO 2005) is an alternative to the Fiat-Shamir transform that enables straight-line extraction when proving knowledge. In this work we focus on the problem of using the Fischlin transform to construct UC-secure zero-knowledge from Sigma protocols, since UC security – that guarantees security under general concurrent composition – requires straight-line (non-rewinding) simulators. We provide a slightly simplified transform that is much easier to understand, and present algorithmic and implementation optimizations that significantly improve the running time. It appears that the main obstacles to the use of Fischlin in practice is its computational cost and implementation complexity (with multiple parameters that need to be chosen). We provide clear guidelines and a simple methodology for choosing parameters, and show that with our optimizations the running-time is far lower than expected. For just one example, on a 2023 MacBook, the cost of proving the knowledge of discrete log with Fischlin is only 0.41ms (on a single core). This is 15 times slower than plain Fiat-Shamir on the same machine, which is a significant multiple but objectively not significant in many applications. We also extend the transform so that it can be applied to batch proofs, and show how this can be much more efficient than individually proving each statement. We hope that this paper will both encourage and help practitioners implement the Fischlin transform where relevant.
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