Differentially Private Aggregation of Distributed Time-Series with Transformation and Encryption
Summary: PASTE enables the first DP aggregation of distributed time-series without a trusted server. Introduces FPA_k to perturb the Fourier transform of query answers, reducing error from Theta(n) to Theta(k); DLPA scales privacy with O(1) per user. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Vibhor Rastogi
- 2. Suman Nath
Incoming Citations (Sorted by Pagerank)
Showing 18 of 18 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 111 | Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release | 2007 | PODS | 0.00047073785 |
| 177 | Limiting Privacy Breaches in Privacy Preserving Data Mining | 2003 | PODS | 0.0003788711 |
| 178 | Boosting the Accuracy of Differentially Private Histograms Through Consistency | 2010 | VLDB | 0.00037697111 |
| 505 | Relationship Privacy: Output Perturbation for Queries with Joins | 2009 | PODS | 0.00021491332 |
| 568 | Practical Privacy: The SuLQ Framework | 2005 | PODS | 0.00019949368 |
| 1,761 | The Boundary Between Privacy and Utility in Data Publishing | 2007 | VLDB | 0.00010651764 |
| 3,783 | Time Series Compressibility and Privacy | 2007 | VLDB | 6.7714995e-05 |
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