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Selective MPC: Distributed Computation of Differentially Private Key-Value Statistics. (arXiv:2107.12407v2 [cs.CR] UPDATED)
Aug. 31, 2022, 1:20 a.m. | Thomas Humphries, Rasoul Akhavan Mahdavi, Shannon Veitch, Florian Kerschbaum
cs.CR updates on arXiv.org arxiv.org
Key-value data is a naturally occurring data type that has not been
thoroughly investigated in the local trust model. Existing local differentially
private (LDP) solutions for computing statistics over key-value data suffer
from the inherent accuracy limitations of each user adding their own noise.
Multi-party computation (MPC) maintains better accuracy than LDP and similarly
does not require a trusted central party. However, naively applying MPC to
key-value data results in prohibitively expensive computation costs. In this
work, we present selective …
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