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Shoal: Query Optimization and Operator Placement for Access Controlled Stream Processing Systems

Abstract : Distributed Data Stream Processing Systems (DDSPS) execute on transient data flowing through long-running, continuous, streaming queries, grouped together in query networks. Often, these continuous queries are outsourced by the querier to third-party computing platforms to help control the cost and maintenance associated with owning and operating such systems. Such outsourcing, however, may be contradictory to a data provider’s access controls as they may not permit their data to be viewed or accessed by an unintended third party. A data provider’s access controls may, therefore, prevent a querier from fully outsourcing their query. Current research in this space has provided alternative access control techniques that involve computation-enabling encryption techniques, specialized hardware, or specialized query operators that allow for a data provider to enforce access controls while still allowing a querier to employ a third-party system. However, no system considers access controls and their enforcement as part of the query optimization step. In this paper, we present Shoal, an optimizer that considers access controls as first class citizens when optimizing and distributing a network of query operators. We show that Shoal can generate more efficient queries versus the state-of-the-art, as well as detail how changes in access controls can generate new query plans at runtime.
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Submitted on : Thursday, November 28, 2019 - 2:26:10 PM
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Cory Thoma, Alexandros Labrinidis, Adam Lee. Shoal: Query Optimization and Operator Placement for Access Controlled Stream Processing Systems. 33th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec), Jul 2019, Charleston, SC, United States. pp.261-280, ⟨10.1007/978-3-030-22479-0_14⟩. ⟨hal-02384602⟩

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