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Time Series Compressibility and Privacy

Summary: Explores the trade-off between time-series compressibility and privacy, formalizing perturbations that mimic original data to avoid detection and preserve structure. Real-data experiments and streaming-ready schemes illustrate practical trade-offs and on-the-fly data hiding with a tunable leakage-utility balance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9790
Venue
VLDB
Year
2007
Pagerank
6.5960717e-05
Overall Rank
4,629 | 68.25%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{papadimitriou_vldb07,
        title = {{Time Series Compressibility and Privacy}},
        author = {Papadimitriou, Spiros and Li, Feifei and Kollios, George and Yu, Philip S.},
        journal = {PVLDB},
        series = {{VLDB} '07},
        volume = {30},
        pages = {459--470},
        year = {2007}
}

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