Abstract
Cloud service providers offer robust infrastructure for rent to organizations of all kinds. High stakes applications, such as the ones in defense and healthcare, are turning to the public cloud for a cost-effective, geographically distributed, always available solution to their hosting needs. Many such users are unwilling or unable to delegate their data to this third-party infrastructure. In this demonstration, we introduce RESCU-SQL, a zero-trust platform for resilient and secure SQL querying outsourced to one or more cloud service providers. RESCU-SQL users can query their DBMS using cloud infrastructure alone without revealing their private records to anyone. It does so by executing the query over secure multiparty computation. We call this system zero trust because it can tolerate any number of malicious servers provided one of them remains honest. Our demo will offer an interactive dashboard with which attendees can observe the performance of RESCU-SQL deployed on several in-cloud nodes for the TPC-H benchmark. Attendees can select a computing party and inject messages from it to explore how quickly it detects and reacts to a malicious party. This is the first SQL system to support all-but-one maliciously secure querying over a semi-honest coordinator for efficiency.
Original language | English (US) |
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Pages (from-to) | 4086-4089 |
Number of pages | 4 |
Journal | Proceedings of the VLDB Endowment |
Volume | 16 |
Issue number | 12 |
DOIs | |
State | Published - 2023 |
Event | 49th International Conference on Very Large Data Bases, VLDB 2023 - Vancouver, Canada Duration: Aug 28 2023 → Sep 1 2023 |
Funding
This work is supported by Air Force Research Lab grant #FA8750-22-2-0156. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Research Laboratory or the U.S. Government. — Approved for Public Release on 26 July 2023. Distribution Is Unlimited. Case Number: AFRL-2023-3625.
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- General Computer Science