2026-07-23T22:06:53Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:20512 2024-08-06T05:20:07Z ddc:004 open_access

Pure-DP Aggregation in the Shuffle Model: Error-Optimal and Communication-Efficient Ghazi, Badih Kumar, Ravi Manurangsi, Pasin Differential Privacy Shuffle Model Aggregation Pure Differential Privacy We obtain a new protocol for binary counting in the ε-DP_shuffle model with error O(1/ε) and expected communication Õ((log n)/ε) messages per user. Previous protocols incur either an error of O(1/ε^1.5) with O_ε(log n) messages per user (Ghazi et al., ITC 2020) or an error of O(1/ε) with O_ε(n²) messages per user (Cheu and Yan, TPDP 2022). Using the new protocol, we obtained improved ε-DP_shuffle protocols for real summation and histograms. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Badih Ghazi and Ravi Kumar and Pasin Manurangsi 2024 Is Part Of LIPIcs, Volume 304, 5th Conference on Information-Theoretic Cryptography (ITC 2024) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ITC.2024.4 urn:nbn:de:0030-drops-205127 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITC.2024.4 eng https://creativecommons.org/licenses/by/4.0/legalcode