## Cryptology ePrint Archive: Report 2019/1229

Transparent SNARKs from DARK Compilers

Benedikt Bünz and Ben Fisch and Alan Szepieniec

Abstract: We construct a new polynomial commitment scheme for univariate and multivariate polynomials over finite fields, with public-coin evaluation proofs that have logarithmic communication and verification cost in the number of coefficients of the polynomial. The underlying technique is a Diophantine Argument of Knowledge (DARK), leveraging integer representations of polynomials and groups of unknown order. Security is shown from the strong RSA and the adaptive root assumption. Moreover, the scheme does not require a trusted setup if instantiated with class groups. We apply this new cryptographic compiler to a restricted class of algebraic linear IOPs in order to obtain doubly-efficient public-coin IPs with succinct communication and witness-extended emulation for any NP relation. Allowing for linear preprocessing, the online verifier's work is logarithmic in the circuit complexity of the relation.

In particular, we obtain quasi-linear prover time when compiling the IOP employed in Sonic (MBKM, CCS 19). Applying the Fiat-Shamir transform in the random oracle model results in a SNARK system with quasi-linear preprocessing, quasi-linear (online) prover time, logarithmic proof size, and logarithmic (online) verification time for arbitrary circuits. The SNARK is also concretely efficient with $7.8$KB proofs ($70\times$ reduction over state of the art) and $75$ms verification time for circuits with 1 million gates. Most importantly, this SNARK is transparent: it does not require a trusted setup. We also obtain zk-SNARKs by applying a variant of our polynomial commitment scheme that is hiding and offers zero-knowledge evaluation proofs. This construction is the first transparent zk-SNARK that has both a practical prover time as well as asymptotically logarithmic proof size and verification time. We call this system *Supersonic*.

Category / Keywords: cryptographic protocols / Zero-Knowledge, SNARK, IOP, RSA, class groups

Date: received 19 Oct 2019, last revised 30 Oct 2019

Contact author: alan at nervos org,benedikt@cs stanford edu,bfisch@cs stanford edu

Available format(s): PDF | BibTeX Citation

Short URL: ia.cr/2019/1229

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