Prover-Efficient Commit-and-Prove Zero-Knowledge SNARKs

Abstract

Succinct non-interactive zero-knowledge arguments of knowledge (Zk-SNARKs) are needed in many applications. Unfortunately, all previous zk-SNARKs for interesting languages are either inefficient for the prover, or are non-adaptive and based on a commitment scheme that depends both on the prover's input and on the language, i.e., they are not commit-and-prove (CaP) SNARKs. We propose a proof-friendly extractable commitment scheme, and use it to construct prover-efficient adaptive CaP succinct zk-SNARKs for different languages, that can all reuse committed data. In new zk-SNARKs, the prover computation is dominated by a linear number of cryptographic operations. We use batch-verification to decrease the verifier's computation; importantly, batch-verification can be used also in QAP-based zk-SNARKs.