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Data sharing opportunities are everywhere, but privacy concerns and regulatory constraints often prevent organizations from fully realizing their value. A private data federation tackles this challenge by enabling secure querying across multiple privately held data stores where only the final results are revealed to anyone. We investigate optimizing relational queries evaluated under secure multiparty computation, which provides strong privacy guarantees but at a significant performance cost. We present Alchemy, a query optimization framework that generalizes conventional optimization techniques to secure query processing over circuits, the most popular paradigm for cryptographic computation protocols. We build atop VaultDB, our open-source framework for oblivious query processing. Alchemy leverages schema information and the query's structure to minimize circuit complexity while maintaining strong security guarantees. Our optimization framework builds incrementally through four synergistic phases: (1) rewrite rules to minimize circuits; (2) cardinality bounding with schema metadata; (3) bushy plan generation; and (4) physical planning with our fine-grained cost model for operator selection and sort reuse. While our work focuses on MPC, our optimization techniques generalize naturally to other secure computation settings. We validated our approach on TPC-H, demonstrating speedups of up to 2 OOM.
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Obladi: Oblivious Serializable Transactions in the Cloud
This paper presents the design and implementation of Obladi, the first system to provide ACID transactions while also hiding access patterns. Obladi uses as its building block oblivious RAM, but turns the demands of supporting transac- tions into a performance opportunity. By executing transac- tions within epochs and delaying commit decisions until an epoch ends, Obladi reduces the amortized bandwidth costs of oblivious storage and increases overall system through- put. These performance gains, combined with new oblivious mechanisms for concurrency control and recovery, allow Obladi to execute OLTP workloads with reasonable through- put: it comes within 5× to 12× of a non-oblivious baseline on the TPC-C, SmallBank, and FreeHealth applications. Latency overheads, however, are higher (70× on TPC-C).
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- Award ID(s):
- 1762015
- PAR ID:
- 10082091
- Date Published:
- Journal Name:
- Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’18)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
