Arithmetic Sketching
Dan Boneh, Elette Boyle, Henry Corrigan-Gibbs, Niv Gilboa, Yuval Ishai
Abstract
This paper introduces arithmetic sketching, an abstraction of a primitive that several previous works use to achieve lightweight, low-communication zero-knowledge verification of secret-shared vectors. An arithmetic sketching scheme for a language consists of (1) a randomized linear function compressing a long input x to a short “sketch,” and (2) a small arithmetic circuit that accepts the sketch if and only if , up to some small error. If the language has an arithmetic sketching scheme with short sketches, then it is possible to test membership in using an arithmetic circuit with few multiplication gates. Since multiplications are the dominant cost in protocols for computation on secret-shared, encrypted, and committed data, arithmetic sketching schemes give rise to lightweight protocols in each of these settings.
Beyond the formalization of arithmetic sketching, our contributions are: – A general framework for constructing arithmetic sketching schemes from algebraic varieties. This framework unifies schemes from prior work and gives rise to schemes for useful new languages and with improved soundness error. – The first arithmetic sketching schemes for languages of sparse vectors: vectors with bounded Hamming weight, bounded norm, and vectors whose few non-zero values satisfy a given predicate. – A method for “compiling” any arithmetic sketching scheme for a language into a low-communication malicious-secure multi-server protocol for securely testing that a client-provided secret-shared vector is in .
We also prove the first nontrivial lower bounds showing limits on the sketch size for certain languages (e.g., vectors of Hamming-weight one) and proving the non-existence of arithmetic sketching schemes for others (e.g., the language of all vectors that contain a specific value).
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Install the CLIlune papers fulltext f5abb345-e833-4e00-8c1c-c4d8b60a112dCited by top-tier papers3
- Private Analytics via Streaming, Sketching, and Silently Verifiable ProofsMayank Rathee, Yuwen Zhang, Henry Corrigan-Gibbs, Raluca Ada PopaS&P 2024 · 8 citations
- PINE: Efficient Verification of a Euclidean Norm Bound of a Secret-Shared VectorGuy N. Rothblum, Eran Omri, Junye Chen, Kunal TalwarUSENIX Security 2024 · 7 citations
- Improved Constructions for Distributed Multi-Point FunctionsElette Boyle, Niv Gilboa, Matan Hamilis, Yuval Ishai et al.S&P 2025
Builds on8
- Function Secret Sharing: Improvements and ExtensionsElette Boyle, Niv Gilboa, Yuval IshaiCCS 2016 · 404 citations
- Scaling ORAM for Secure ComputationJack Doerner, Abhi ShelatCCS 2017 · 221 citations
- Function Secret Sharing for Mixed-Mode and Fixed-Point Secure ComputationElette Boyle, Nishanth Chandran, Niv Gilboa, Divya Gupta et al.EUROCRYPT 2021 · 135 citations
- Lightweight Techniques for Private Heavy HittersDan Boneh, Elette Boyle, Henry Corrigan-Gibbs, Niv Gilboa et al.S&P 2021 · 134 citations
- Express: Lowering the Cost of Metadata-hiding Communication with Cryptographic PrivacySaba Eskandarian, Henry Corrigan-Gibbs, Matei Zaharia, Dan BonehUSENIX Security 2021 · 98 citations
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