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The Adversarial Robustness of Sampling

Summary: Shows Bernoulli/reservoir sampling in streaming is vulnerable to fully adaptive adversaries that inspect the current sample—VC-dimension bounds can fail and sublinear samples become unrepresentative. Fix: replace d by log|R|; sample size Ω(log|R|/ε^2) suffices (nearly tight), while exploitable attacks require exponentially large |R|. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1806
Venue
PODS
Year
2020
Pagerank
6.8299006e-05
Overall Rank
4,211 | 71.11%
DOI
10.1145/3375395.3387643

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{beneliezer_pods20,
        address = {New York, NY, USA},
        series = {{PODS} '20},
        title = {{The Adversarial Robustness of Sampling}},
        url = {https://dl.acm.org/doi/10.1145/3375395.3387643},
        doi = {10.1145/3375395.3387643},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Ben-Eliezer, Omri and Yogev, Eylon},
        year = {2020}
}

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