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Privacy at Scale: Local Differential Privacy in Practice

Summary: Local differential privacy at Internet scale: deployments by Google, Apple, Microsoft for telemetry. Survey theory and algorithms; discuss data-management implications and open directions for scalable privacy analytics without a trusted server. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5589
Venue
SIGMOD
Year
2018
Pagerank
7.9443198e-05
Overall Rank
2,899 | 79.84%
DOI
10.1145/3183713.3197390

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Showing 13 of 13 citing papers.

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Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
177 Limiting Privacy Breaches in Privacy Preserving Data Mining 2003 PODS 0.0003788711
1,930 Marginal Release Under Local Differential Privacy 2018 SIGMOD 0.00010040732
3,843 Privacy via Pseudorandom Sketches 2006 PODS 6.7077542e-05
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