Publications

Adaptively-Sound Succinct Arguments for NP from Indistinguishability Obfuscation

Brent Waters and David J. Wu

Annual ACM Symposium on Theory of Computing (STOC), 2024

Resources

Abstract

A succinct non-interactive argument (SNARG) for \( \mathsf{NP} \) allows a prover to convince a verifier that an \( \mathsf{NP} \) statement \( x \) is true with a proof of size \( o(|x| + |w|) \), where \( w \) is the associated \( \mathsf{NP} \) witness. A SNARG satisfies adaptive soundness if the malicious prover can choose the statement to prove after seeing the scheme parameters. In this work, we provide the first adaptively-sound SNARG for \( \mathsf{NP} \) in the plain model assuming sub-exponentially-hard indistinguishability obfuscation, sub-exponentially-hard one-way functions, and either the (polynomial) hardness of the discrete log assumption or the (polynomial) hardness of factoring. This gives the first adaptively-sound SNARG for \( \mathsf{NP} \) from falsifiable assumptions. All previous SNARGs for \( \mathsf{NP} \) in the plain model either relied on non-falsifiable cryptographic assumptions or satisfied a weak notion of non-adaptive soundness (where the adversary has to choose the statement it proves before seeing the scheme parameters).

BibTeX
@inproceedings{WW24,
  author    = {Brent Waters and David J. Wu},
  title     = {Adaptively-Sound Succinct Arguments for {NP} from Indistinguishability Obfuscation},
  booktitle = {{STOC}},
  year      = {2024}
}