Welcome to the resource topic for 2021/750
Title:
Appenzeller to Brie: Efficient Zero-Knowledge Proofs for Mixed-Mode Arithmetic and \mathbb{Z}_{2^k}
Authors: Carsten Baum, Lennart Braun, Alexander Munch-Hansen, Benoit Razet, Peter Scholl
Abstract:Zero-knowledge proofs are highly flexible cryptographic protocols that are an important building block for many secure systems. Typically, these are defined with respect to statements that are formulated as arithmetic operations over a fixed finite field. This inflexibility is a disadvantage when it comes to complex programs, as some fields are more amenable to express certain operations than others. At the same time, there do not seem to be many proofs with a programming model similar to those found in modern computer architectures that perform arithmetic with 32 or 64 bit integers. In this work, we present solutions to both of these problems. First, we show how to efficiently check consistency of secret values between different instances of zero-knowledge protocols based on the commit-and-prove paradigm. This allows a protocol user to easily switch to the most efficient representation for a given task. To achieve this, we modify the extended doubly-authenticated bits (edabits) approach by Escudero et al. (Crypto 2020), originally developed for MPC, and optimize it for the zero-knowledge setting. As an application of our consistency check, we also introduce protocols for efficiently verifying truncations and comparisons of shared values both modulo a large prime p and modulo 2^k. Finally, we complement our conversion protocols with new protocols for verifying arithmetic statements in \mathbb{Z}_{2^k}. Here, we build upon recent interactive proof systems based on information-theoretic MACs and vector oblivious linear evaluation (VOLE), and show how this paradigm can be adapted to the ring setting. In particular, we show that supporting such modular operations natively in a proof system can be almost as efficient as proofs over large fields or bits, and this also easily plugs into our framework for zero-knowledge conversions.
ePrint: https://eprint.iacr.org/2021/750
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