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Ali Kakhbod is an assistant professor in the Finance Group at the Haas School of Business, UC Berkeley. Previously, he received a PhD in Economics from the Massachusetts Institute of Technology (MIT) and a PhD in EECS (Electrical Engineering and Computer...
Dmitry Livdan is a Professor of Finance at Haas School of Business. His research expertise and interests are in Corporate Finance, Asset Pricing, and Market Microstructure.
We construct an adaptively-sound succinct non-interactive argument (SNARG) for NP in the CRS model from sub-exponentially-secure indistinguishability obfuscation (iO) 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 iO.
Abstract not available.