Privacy Amplification via Shuffled Check-Ins
- URL: http://arxiv.org/abs/2206.03151v2
- Date: Tue, 4 Jul 2023 06:28:47 GMT
- Title: Privacy Amplification via Shuffled Check-Ins
- Authors: Seng Pei Liew, Satoshi Hasegawa, Tsubasa Takahashi
- Abstract summary: We study a protocol for distributed computation called shuffled check-in.
It achieves strong privacy guarantees without requiring any further trust assumptions beyond a trusted shuffler.
We show that shuffled check-in achieves tight privacy guarantees through privacy amplification.
- Score: 2.3333090554192615
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We study a protocol for distributed computation called shuffled check-in,
which achieves strong privacy guarantees without requiring any further trust
assumptions beyond a trusted shuffler. Unlike most existing work, shuffled
check-in allows clients to make independent and random decisions to participate
in the computation, removing the need for server-initiated subsampling.
Leveraging differential privacy, we show that shuffled check-in achieves tight
privacy guarantees through privacy amplification, with a novel analysis based
on R{\'e}nyi differential privacy that improves privacy accounting over
existing work. We also introduce a numerical approach to track the privacy of
generic shuffling mechanisms, including Gaussian mechanism, which is the first
evaluation of a generic mechanism under the distributed setting within the
local/shuffle model in the literature. Empirical studies are also given to
demonstrate the efficacy of the proposed approach.
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