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Sonic: Zero-Knowledge SNARKs from Linear-Size Universal and Updatable Structured Reference Strings

Maller, M; Bowe, S; Kohlweiss, M; Meiklejohn, S; (2019) Sonic: Zero-Knowledge SNARKs from Linear-Size Universal and Updatable Structured Reference Strings. In: CCS '19: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security. (pp. pp. 2111-2128). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

Ever since their introduction, zero-knowledge proofs have become an important tool for addressing privacy and scalability concerns in a variety of applications. In many systems each client downloads and verifies every new proof, and so proofs must be small and cheap to verify. The most practical schemes require either a trusted setup, as in (pre-processing) zk-SNARKs, or verification complexity that scales linearly with the complexity of the relation, as in Bulletproofs. The structured reference strings required by most zk-SNARK schemes can be constructed with multi-party computation protocols, but the resulting parameters are specific to an individual relation. Groth et al. discovered a zk-SNARK protocol with a universal structured reference string that is also updatable, but the string scales quadratically in the size of the supported relations. Here we describe a zero-knowledge SNARK, Sonic, which supports a universal and continually updatable structured reference string that scales linearly in size. We also describe a generally useful technique in which untrusted "helpers" can compute advice that allows batches of proofs to be verified more efficiently. Sonic proofs are constant size, and in the "helped" batch verification context the marginal cost of verification is comparable with the most efficient SNARKs in the literature.

Type: Proceedings paper
Title: Sonic: Zero-Knowledge SNARKs from Linear-Size Universal and Updatable Structured Reference Strings
Event: ACM SIGSAC Conference on Computer and Communications Security (CCS)
Location: London, ENGLAND
Dates: 11 November 2019 - 15 November 2019
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3319535.3339817
Publisher version: https://doi.org/10.1145/3319535.3339817
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10115265
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