Sonic: Zero-Knowledge SNARKs from Linear-Size Universal and Updatable Structured Reference Strings
By Mary Maller, Sean Bowe, Markulf Kohlweiss, Sarah Meiklejohn. IACR Cryptology ePrint Archive, 2019
417 citations recorded by the source corpus.
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.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/2ac167785e327e4e74b754265c6fd92542963353
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Citations in the corpus
- Spartan: Efficient and general-purpose zkSNARKs without trusted setup (2020, methodology): “To cope with trusted setup, recent works [65, 81] propose schemes to update the structured common reference string after it is generated.”