2013Unpublished venueRequires access

Lightweight Zero-Knowledge Proofs for Crypto-Computing Protocols.

Sven Laur, Bingsheng Zhang

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Abstract

Abstract Crypto-computing is a set of well-known techniques for com-puting with encrypted data. The security of the corresponding proto-cols are usually proven in the semi-honest model. In this work, we pro-pose a new class of zero-knowledge proofs, which are tailored for crypto-computing protocols. First, these proofs directly employ properties of the underlying crypto systems and thus many facts have more concise proofs compared to generic solutions. Second, we show how to achieve univer-sal composability in the trusted set-up model where all zero-knowledge proofs share the same system-wide parameters. Third, we derive a new protocol for multiplicative relations and show how to combine it with several crypto-computing frameworks.

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What this paper is about

Abstract Crypto-computing is a set of well-known techniques for com-puting with encrypted data. The security of the corresponding proto-cols are usually proven in the semi-honest model. In this work, we pro-pose a new class of zero-knowledge proofs, which are tailored for crypto-computing protocols. First, these proofs directly employ properties of the underlying crypto systems and thus many facts have more concise proofs compared to generic solutions. Second, we show how to achieve univer-sal composability in the trusted set-up model where all zero-knowledge proofs share the same system-wide parameters. Third, we derive a new protocol for multiplicative relations and show how to combine it with several crypto-computing frameworks.

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Available abstract

Abstract Crypto-computing is a set of well-known techniques for com-puting with encrypted data. The security of the corresponding proto-cols are usually proven in the semi-honest model. In this work, we pro-pose a new class of zero-knowledge proofs, which are tailored for crypto-computing protocols. First, these proofs directly employ properties of the underlying crypto systems and thus many facts have more concise proofs compared to generic solutions. Second, we show how to achieve univer-sal composability in the trusted set-up model where all zero-knowledge proofs share the same system-wide parameters. Third, we derive a new protocol for multiplicative relations and show how to combine it with several crypto-computing frameworks.

Key concepts: Mathematical proof, Zero-knowledge proof, Computer science, Universal composability, Protocol (science), Theoretical computer science, Set (abstract data type), Composability

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