[Resource Topic] 2022/670: Practical UC-Secure Zero-Knowledge Smart Contracts

Welcome to the resource topic for 2022/670

Title:
Practical UC-Secure Zero-Knowledge Smart Contracts

Authors: Jayamine Alupotha and Xavier Boyen

Abstract:

Zero-knowledge defines that verifier(s) learns nothing but predefined statement(s); e.g., verifiers learn nothing except the program’s path for the respective transaction in a zero-knowledge contract program. Intra-Privacy or insiders’ zero-knowledge — ability to maintain a secret in a multi-party computation — is an essential security property for smart contracts of Confidential Transactions (CT). Otherwise, the users have to reveal their confidential coin amounts to each other even if it is not a condition of the contract, contradicting the idea of zero-knowledge. For example, in an escrow contract, the escrow should not learn buyers’ or sellers’ account balances if the escrow has to pay into their accounts. Current private computational platforms, including homomorphic encryption and (ZK-)SNARK, can not be used in CT’s smart contracts because homomorphic encryption requires secret key sharing, and (ZK-)SNARK requires a different setup for each computation which has to be stored on the blockchain. Existing private smart contracts are not intra-private even though they are inter-private — participants can maintain secrets from verifiers but not from other participants, accordingly. To fill this research gap, we introduce the notion of Confidential Integer Processing'' (CIP) with two intra-private single-setup zero-knowledge programming protocols, (1) CIP-DLP’’ from the Discrete Log Problem (DLP) targeting Ring/Aggregable CT like Monero and Mimblewimble, and (2) ``CIP-SIS’’ from Approximate (Ring-Modular-) Short Integer Solution Problem (Approx-SIS) aiming at lattice-based Ring/Aggregable CT. To the best of our knowledge, our CIP protocols are the first practical public zero-knowledge contract protocols that are also secure under the Universal Composability (UC) framework without any hardware magic or trusted offline computations.

ePrint: https://eprint.iacr.org/2022/670

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