FAST: Differentially Private Real-Time Aggregate Monitor with Filtering and Adaptive Sampling
Summary: FAST enables real-time differentially private sharing of aggregate time-series data using filtering and adaptive sampling. Adaptive strategies boost utility under DP for streaming and live data, enabling practical DP analytics on SIGMOD'13 datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Liyue Fan (Emory University)
- 2. Li Xiong (Emory University)
- 3. Vaidy Sunderam (Emory University)
BibTeX Citation
@inproceedings{fan_sigmod13,
title = {{FAST: Differentially Private Real-Time Aggregate Monitor with Filtering and Adaptive Sampling}},
author = {Fan, Liyue and Xiong, Li and Sunderam, Vaidy},
series = {{SIGMOD} '13},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2463676.2465253},
url = {https://dl.acm.org/doi/10.1145/2463676.2465253},
year = {2013}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,571 | Benchmarking the Utility of w-event Differential Privacy Mechanisms - When Baselines Become Mighty Competitors | 2023 | VLDB | 5.4940407e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 64 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00038522486 |
| 732 | Differentially Private Aggregation of Distributed Time-Series with Transformation and Encryption | 2010 | SIGMOD | 0.00014383875 |
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