Polynomial Commitment with a One-to-Many Prover and Applications
Jiaheng Zhang, Tiancheng Xie, Thang Hoang, Elaine Shi, Yupeng Zhang
摘要
Verifiable Secret Sharing (VSS) is a foundational cryptographic primitive that serves as an essential building block in multi-party computation and decentralized blockchain applications. One of the most practical ways to construct VSS is through a polynomial commitment, where the dealer commits to a random polynomial whose 0-th coefficient encodes the secret to be shared, and proves the evaluation of the committed polynomial at a different point to each of N verifiers, i.e., the polynomial commitment is used in a "one-to-many" fashion. The recent work of Tomescu et al. (IEEE S&P 2020) was the first to consider polynomial commitment with "one-tomany prover batching", such that the prover can prove evaluations at N different points at the cost of O(1) proofs. However, their scheme is not optimal and requires a trusted setup. In this paper, we asymptotically improve polynomial commitment with one-to-many prover batching. We propose two novel schemes. First, we propose a scheme with optimal asymptotics in all dimensions in the trusted setup setting. Second, we are the first to consider one-to-many prover batching for transparent polynomial commitments, and we propose a transparent scheme whose performance approximately matches the best-known scheme in the trusted setup setting. We implement our schemes and evaluate their performance. Our scheme in the trusted setup setting improves the proof size by 20× and the verifier time by 7.8× for 2 21 parties, with a small overhead on the prover time. Our transparent polynomial commitment removes the trusted setup and further improves the prover time by 2.3×.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper9
- zkBridge: Trustless Cross-chain Bridges Made PracticalTiancheng Xie, Jiaheng Zhang, Zerui Cheng, Fan Zhang 等CCS 2022 · 被引用 131 次
- Pianist: Scalable zkRollups via Fully Distributed Zero-Knowledge ProofsTianyi Liu, Tiancheng Xie, Jiaheng Zhang, Dawn Song 等S&P 2024 · 被引用 52 次
- Fast RS-IOP Multivariate Polynomial Commitments and Verifiable Secret SharingZongyang Zhang, Weihan Li, Yanpei Guo, Kexin Shi 等USENIX Security 2024 · 被引用 9 次
- Scalable and Adaptively Secure Any-Trust Distributed Key Generation and All-hands CheckpointingHanwen Feng, Tiancheng Mai, Qiang TangCCS 2024 · 被引用 4 次
- Distributed Vector Commitments and Their ApplicationsRui Gao, Huaqun Wang, Zhiguo Wan, Yuncong HuUSENIX Security 2026
它引用的顶会 Paper9
- Doubly-Efficient zkSNARKs Without Trusted SetupRiad S. Wahby, Ioanna Tzialla, Abhi Shelat, Justin Thaler 等S&P 2018 · 被引用 356 次
- Transparent SNARKs from DARK CompilersBenedikt Bünz, Ben Fisch, Alan SzepieniecEUROCRYPT 2020 · 被引用 240 次
- vSQL: Verifying Arbitrary SQL Queries over Dynamic Outsourced DatabasesYupeng Zhang, Daniel Genkin, Jonathan Katz, Dimitrios Papadopoulos 等S&P 2017 · 被引用 206 次
- Transparent Polynomial Delegation and Its Applications to Zero Knowledge ProofJiaheng Zhang, Tiancheng Xie, Yupeng Zhang, Dawn SongS&P 2020 · 被引用 192 次
- Asynchronous Distributed Key Generation for Computationally-Secure Randomness, Consensus, and Threshold SignaturesEleftherios Kokoris-Kogias, Dahlia Malkhi, Alexander SpiegelmanCCS 2020 · 被引用 107 次
相关 Paper
- hbACSS: How to Robustly Share Many SecretsThomas Yurek, Licheng Luo, Jaiden Fairoze, Aniket Kate 等NDSS 2022
- UltraProofs: Scalable Reed-Solomon Code CommitmentYanpei Guo, Alex Luoyuan Xiong, Wenjie Qu, Jiaheng ZhangS&P 2026
- Concretely Efficient Lattice-Based Polynomial Commitment from Standard AssumptionsIntak Hwang, Jinyeong Seo, Yongsoo SongCRYPTO 2024 · 被引用 9 次
- DewTwo: A Transparent PCS with Quasi-Linear Prover, Logarithmic Verifier and 4.5KB Proofs from Falsifiable AssumptionsBenedikt Bünz, Tushar Mopuri, Alireza Shirzad, Sriram SridharCRYPTO 2025 · 被引用 1 次
- HydraProofs: Optimally Computing All Proofs in a Vector Commitment (With Applications to Efficient zkSNARKs Over Data from Multiple Users)Christodoulos Pappas, Dimitrios Papadopoulos, Charalampos PapamanthouS&P 2025
