Paper 2024/940

Scalable Collaborative zk-SNARK and Its Application to Efficient Proof Outsourcing

Xuanming Liu, Zhejiang University
Zhelei Zhou, Zhejiang University
Yinghao Wang, Zhejiang University
Jinye He, National University of Singapore
Bingsheng Zhang, Zhejiang University
Xiaohu Yang, Zhejiang University
Jiaheng Zhang, National University of Singapore
Abstract

Collaborative zk-SNARK (USENIX'22) allows multiple parties to jointly create a zk-SNARK proof over distributed secrets (also known as the witness). It provides a promising approach to proof outsourcing, where a client wishes to delegate the tedious task of proof generation to many servers from different locations, while ensuring no corrupted server can learn its witness (USENIX'23). Unfortunately, existing work remains a significant efficiency problem, as the protocols rely heavily on a particularly powerful server, and thus face challenges in achieving scalability for complex applications. In this work, we address this problem by extending the existing zk-SNARKs Libra (Crypto'19) and HyperPlonk (Eurocrypt'23) into scalable collaborative zk-SNARKs. Crucially, our collaborative proof generation does not require a powerful server, and all servers take up roughly the same proportion of the total workload. In this way, we achieve privacy and scalability simultaneously for the first time in proof outsourcing. To achieve this, we develop an efficient MPC toolbox for a number of useful multivariate polynomial primitives, including sumcheck, productcheck, and multilinear polynomial commitment, which can also be applied to other applications as independent interests. For proof outsourcing purposes, when using $128$ servers to jointly generate a proof for a circuit size of $2^{24}$ gates, our benchmarks for these two collaborative proofs show a speedup of $21\times$ and $24\times$ compared to a local prover, respectively. Furthermore, we are able to handle enormously large circuits, making it practical for real-world applications.

Note: This work is an extensive update of a previous work, which can be found at https://eprint.iacr.org/2024/143. The update includes semi-honest protocols for collaborative HyperPlonk, sub-protocol used by collaborative Libra, additional optimizations, and new experimental results.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Preprint.
Keywords
zero-knowledgezk-SNARKsmulti-party computationimplementation
Contact author(s)
hinsliu @ zju edu cn
yangxh @ zju edu cn
jhzhang @ nus edu sg
History
2024-06-12: approved
2024-06-12: received
See all versions
Short URL
https://ia.cr/2024/940
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2024/940,
      author = {Xuanming Liu and Zhelei Zhou and Yinghao Wang and Jinye He and Bingsheng Zhang and Xiaohu Yang and Jiaheng Zhang},
      title = {Scalable Collaborative zk-{SNARK} and Its Application to Efficient Proof Outsourcing},
      howpublished = {Cryptology {ePrint} Archive, Paper 2024/940},
      year = {2024},
      url = {https://eprint.iacr.org/2024/940}
}
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