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Title:
A Pure Indistinguishability Obfuscation Approach to Adaptively-Sound SNARGs for NP
Authors: Brent Waters, David J. Wu
Abstract:We construct an adaptively-sound succinct non-interactive argument (SNARG) for NP in the CRS model from sub-exponentially-secure indistinguishability obfuscation (i\mathcal{O}) and sub-exponentially-secure one-way functions. Previously, Waters and Wu (STOC 2024), and subsequently, Waters and Zhandry (CRYPTO 2024) showed how to construct adaptively-sound SNARGs for NP by relying on sub-exponentially-secure indistinguishability obfuscation, one-way functions, and an additional algebraic assumption (i.e., discrete log, factoring, or learning with errors). In this work, we show that no additional algebraic assumption is needed and vanilla (sub-exponentially-secure) one-way functions already suffice in combination with i\mathcal{O}.
We first give a direct construction of an adaptively-sound SNARG for NP assuming (sub-exponentially-secure) i\mathcal{O} and an injective one-way function. Then, we show that it suffices to have an injective one-way function that has an inefficient sampler (i.e., sampling a challenge for the one-way function requires super-polynomial time). Because we rely on the existence of injective one-way functions only in the security proof and not in the actual construction, having an inefficient sampling procedure does not impact correctness. We then show that injective one-way functions with an inefficient sampler can be built generically from any vanilla one-way function. Our approach may be independently useful in other settings to replace injective one-way functions with standard one-way functions in applications of i\mathcal{O}.
ePrint: https://eprint.iacr.org/2024/933
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