SPECIAL: SynoPsis AssistEd Secure CollaboratIve AnaLytics
Summary: SPECIAL uses one-time DP-funded private synopses to index encrypted data and enable pre-runtime cost-based planning without further privacy loss. One-sided noise and private bounds ensure lossless multi-join processing with bounded privacy, dramatically improving SCA performance. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Chenghong Wang (Indiana University)
- 2. Lina Qiu (Boston University)
- 3. Johes Bater (Tufts University)
- 4. Yukui Luo (University of Massachusetts Dartmouth)
BibTeX Citation
@article{wang_vldb25,
title = {{SPECIAL: SynoPsis AssistEd Secure CollaboratIve AnaLytics}},
author = {Wang, Chenghong and Qiu, Lina and Bater, Johes and Luo, Yukui},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {4},
pages = {1035--1048},
doi = {10.14778/3717755.3717764},
url = {https://doi.org/10.14778/3717755.3717764},
year = {2025}
}
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