This content will become publicly available on April 30, 2025
Data Discovery and Indexing for Semi-Structured Scientific Data [Data Discovery and Indexing for Semi-Structured Scientific Data]
- Award ID(s):
- 2215789
- PAR ID:
- 10545717
- Publisher / Repository:
- SCITEPRESS - Science and Technology Publications
- Date Published:
- ISBN:
- 978-989-758-692-7
- Page Range / eLocation ID:
- 264 to 271
- Format(s):
- Medium: X
- Location:
- Angers, France
- Sponsoring Org:
- National Science Foundation
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null (Ed.)We introduce a new technique for indexing joins in encrypted SQL databases called partially precomputed joins which achieves lower leakage and bandwidth than those used in prior constructions. These techniques are incorporated into state-of-the-art structured encryption schemes for SQL data, yielding a hybrid indexing scheme with both partially and fully precomputed join indexes. We then introduce the idea of leakage-aware query planning by giving a heuristic that helps the client decide, at query time, which index to use so as to minimize leakage and stay below a given bandwidth budget. We conclude by simulating our constructions on real datasets, showing that our heuristic is accurate and that partially-precomputed joins perform well in practice.more » « less