Investigating Privacy-Aware Distributed Query Evaluation

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Provided by: Association for Computing Machinery
Topic: Security
Format: PDF
Historically, privacy and efficiency have largely been at odds with one another when querying remote data sources: traditional query optimization techniques provide efficient retrieval by exporting information about the intension of a query to data sources, while Private Information Retrieval (PIR) schemes hide query intension at the cost of extreme computational or communication overheads. Given the increasing use of internet-scale distributed databases, exploring the spectrum between these two extremes is worthwhile. In this paper, the authors explore the degree to which query intension is leaked to remote data sources when a variety of existing query processing and view materialization techniques are used.
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