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Differentially Private Summation with Multi-Message Shuffling

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arxiv 1906.09116 v3 pith:2TVNKZBC submitted 2019-06-20 cs.CR stat.ML

classification cs.CRstat.ML
keywords partyprotocolsummationepsilonerrormessagesmodelcheu
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abstract

In recent work, Cheu et al. (Eurocrypt 2019) proposed a protocol for $n$-party real summation in the shuffle model of differential privacy with $O_{\epsilon, \delta}(1)$ error and $\Theta(\epsilon\sqrt{n})$ one-bit messages per party. In contrast, every local model protocol for real summation must incur error $\Omega(1/\sqrt{n})$, and there exist protocols matching this lower bound which require just one bit of communication per party. Whether this gap in number of messages is necessary was left open by Cheu et al. In this note we show a protocol with $O(1/\epsilon)$ error and $O(\log(n/\delta))$ messages of size $O(\log(n))$ per party. This protocol is based on the work of Ishai et al.\ (FOCS 2006) showing how to implement distributed summation from secure shuffling, and the observation that this allows simulating the Laplace mechanism in the shuffle model.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. On the Power of Multiple Anonymous Messages

    cs.CR 2019-08 accept novelty 8.0 of 10

    Single-message shuffled-model frequency estimation has optimal error about min(n^{1/4}, sqrt(B)); multi-message protocols achieve polylogarithmic error with polylogarithmic communication.

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