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ECLIPSE: Enhanced Compiling method for Pedersen-committed zkSNARK Engines

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

We advance the state-of-the art for zero-knowledge commit-and-prove SNARKs (CP-SNARKs). CP-SNARKs are an important class of SNARKs which, using commitments as “glue”, allow to efficiently combine proof systems—e.g., general-purpose SNARKs (an efficient way to prove statements about circuits) and Σ -protocols (an efficient way to prove statements about group operations). Thus, CP-SNARKs allow to efficiently provide zero-knowledge proofs for composite statements such as h= H(g x) for some hash-function H. Our main contribution is providing the first construction of CP-SNARKs where the proof size is succinct in the number of commitments. We achieve our result by providing a general technique to compile Algebraic Holographic Proofs (AHP) (an underlying abstraction used in many modern SNARKs) with special “decomposition” properties into an efficient CP-SNARK. We then show that some of the most efficient AHP constructions—Marlin, PLONK, and Sonic—satisfy our compilation requirements. Our resulting SNARKs achieve universal and updatable reference strings, which are highly desirable features as they greatly reduce the trust needed in the SNARK setup phase.

Original languageEnglish
Title of host publicationPublic-Key Cryptography – PKC 2022 : 25th IACR International Conference on Practice and Theory of Public-Key Cryptography
EditorsGoichiro Hanaoka, Junji Shikata, Yohei Watanabe
Number of pages31
Place of publicationCham
PublisherSpringer
Publication year2022
Pages584-614
ISBN (print)9783030971205
DOIs
Publication statusPublished - 2022
Event25th IACR International Conference on Practice and Theory of Public-Key Cryptography, PKC 2022 - Virtual, Online
Duration: 8 Mar 202211 Mar 2022

Conference

Conference25th IACR International Conference on Practice and Theory of Public-Key Cryptography, PKC 2022
ByVirtual, Online
Periode08/03/202211/03/2022
SeriesLecture Notes in Computer Science
Volume13177
ISSN0302-9743

    Research areas

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