Less is more: refinement proofs for probabilistic proofs
Kunming Jiang, Devora Chait-Roth, Zachary DeStefano, Michael Walfish, Thomas Wies
摘要
There has been intense interest over the last decade in implementations of probabilistic proofs (IPs, SNARKs, PCPs, and so on): protocols in which an untrusted party proves to a verifier that a given computation was executed properly, possibly in zero knowledge. Nevertheless, implementations still do not scale beyond small computations. A central source of overhead is the front-end: translating from the abstract computation to a set of equivalent arithmetic constraints. This paper introduces a general-purpose framework, called Distiller, in which a user translates to constraints not the original computation but an abstracted specification of it. Distiller is the first in this area to perform such transformations in a way that is provably safe. Furthermore, by taking the idea of "encode a check in the constraints" to its literal logical extreme, Distiller exposes many new opportunities for constraint reduction, resulting in cost reductions for benchmark computations of 1.3–50×, and in some cases, better asymptotics.
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引用它的顶会 Paper3
- Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsSebastian Angel, Eleftherios Ioannidis, Elizabeth Margolin, Srinath T. V. Setty 等USENIX Security 2024 · 被引用 12 次
- Spain: Succinct Proofs for Numerical ComputationsZachary DeStefano, Noah Golub, Zile Huang, Julius Zhang 等OSDI 2026
- CoBBL: Dynamic Constraint Generation for SNARKsKunming Jiang, Fraser Brown, Riad S. WahbyS&P 2025
它引用的顶会 Paper17
- Sonic: Zero-Knowledge SNARKs from Linear-Size Universal and Updatable Structured Reference StringsMary Maller, Sean Bowe, Markulf Kohlweiss, Sarah MeiklejohnCCS 2019 · 被引用 412 次
- Marlin: Preprocessing zkSNARKs with Universal and Updatable SRSAlessandro Chiesa, Yuncong Hu, Mary Maller, Pratyush Mishra 等EUROCRYPT 2020 · 被引用 356 次
- Spartan: Efficient and General-Purpose zkSNARKs Without Trusted SetupSrinath T. V. SettyCRYPTO 2020 · 被引用 262 次
- ZEXE: Enabling Decentralized Private ComputationSean Bowe, Alessandro Chiesa, Matthew Green, Ian Miers 等S&P 2020 · 被引用 257 次
- Wolverine: Fast, Scalable, and Communication-Efficient Zero-Knowledge Proofs for Boolean and Arithmetic CircuitsChenkai Weng, Kang Yang, Jonathan Katz, Xiao WangS&P 2021 · 被引用 205 次
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