RASP-QS: Efficient and Confidential Query Services in the Cloud
Summary: Prototype for efficient and confidential range/kNN queries on cloud data using random space perturbation (RASP). RASP offers practical cloud privacy and faster query processing than encryption-based methods, demonstrated with an interactive visual interface to explore its merits. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Zohreh Alavi (Wright State University)
- 2. Lu Zhou (Wright State University)
- 3. James Powers (Wright State University)
- 4. Keke Chen (Wright State University)
BibTeX Citation
@article{alavi_vldb14,
title = {{RASP-QS: Efficient and Confidential Query Services in the Cloud}},
author = {Alavi, Zohreh and Zhou, Lu and Powers, James and Chen, Keke},
journal = {PVLDB},
series = {{VLDB} '14},
volume = {7},
number = {13},
pages = {1685--1688},
doi = {10.14778/2733004.2733061},
url = {https://doi.org/10.14778/2733004.2733061},
year = {2014}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 310 | Order Preserving Encryption for Numeric Data | 2004 | SIGMOD | 0.00021766789 |
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