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Chained-DP: Can We Recycle Privacy Budget?. (arXiv:2309.07075v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Privacy-preserving vector mean estimation is a crucial primitive in federated
analytics. Existing practices usually resort to Local Differentiated Privacy
(LDP) mechanisms that inject random noise into users' vectors when
communicating with users and the central server. Due to the privacy-utility
trade-off, the privacy budget has been widely recognized as the bottleneck
resource that requires well-provisioning. In this paper, we explore the
possibility of privacy budget recycling and propose a novel Chained-DP
framework enabling users to carry out data aggregation sequentially …
analytics budget federated analytics inject local noise practices privacy random recycle server trade utility