Eos: Efficient Private Delegation of zkSNARK Provers
Alessandro Chiesa, Ryan Lehmkuhl, Pratyush Mishra, Yinuo Zhang
摘要
Succinct zero knowledge proofs (i.e. zkSNARKs) are powerful cryptographic tools that enable a prover to convince a verifier that a given statement is true without revealing any additional information. Their attractive privacy properties have led to much academic and industrial interest. Unfortunately, existing systems for generating zkSNARKs are expensive, which limits the applications in which these proofs can be used. One approach is to take advantage of powerful cloud servers to generate the proof. However, existing techniques for this (e.g., DIZK) sacrifice privacy by revealing secret information to the cloud machines. This is problematic for many applications of zkSNARKs, such as decentralized private currency and computation systems. In this work we design and implement privacy-preserving delegation protocols for zkSNARKs with universal setup. Our protocols enable a prover to outsource proof generation to a set of workers, so that if at least one worker does not collude with other workers, no private information is revealed to any worker. Our protocols achieve security against malicious workers without relying on heavyweight cryptographic tools. We implement and evaluate our delegation protocols for a state-of-the-art zkSNARK in a variety of computational and bandwidth settings, and demonstrate that our protocols are concretely efficient. When compared to local proving, using our protocols to delegate proof generation from a recent smartphone (a) reduces end-to-end latency by up to 26×, (b) lowers the delegator's active computation time by up to 1447×, and (c) enables proving up to 256× larger instances.
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引用它的顶会 Paper8
- SoK: What don't we know? Understanding Security Vulnerabilities in SNARKsStefanos Chaliasos, Jens Ernstberger, David Theodore, David Wong 等USENIX Security 2024 · 被引用 32 次
- zkLogin: Privacy-Preserving Blockchain Authentication with Existing CredentialsFoteini Baldimtsi, Konstantinos Kryptos Chalkias, Yan Ji, Jonas Lindstrøm 等CCS 2024 · 被引用 21 次
- Cirrus: Performant and Accountable Distributed SNARKWenhao Wang, Fangyan Shi, Dani Vilardell, Fan ZhangNDSS 2026 · 被引用 11 次
- Siniel: Distributed Privacy-Preserving zkSNARKYunbo Yang, Yuejia Cheng, Kailun Wang, Xiaoguo Li 等NDSS 2025
- zkSaaS: Zero-Knowledge SNARKs as a ServiceSanjam Garg, Aarushi Goel, Abhishek Jain, Guru-Vamsi Policharla 等USENIX Security 2023
它引用的顶会 Paper14
- Hawk: The Blockchain Model of Cryptography and Privacy-Preserving Smart ContractsAhmed E. Kosba, Andrew Miller, Elaine Shi, Zikai Wen 等S&P 2016 · 被引用 2,201 次
- Bulletproofs: Short Proofs for Confidential Transactions and MoreBenedikt Bünz, Jonathan Bootle, Dan Boneh, Andrew Poelstra 等S&P 2018 · 被引用 1,285 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
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