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Authorization-Aware Optimization for Multi-Provider Queries

DocUID: 2019-001 Full Text: PDF

Author: Ekaterina B. Dimitrova, Panos K. Chrysanthis, Adam J. Lee

Abstract: The sharing of sensitive personal information via cloud platforms motivates the need for measures that aim to minimize information leakage to unauthorized users. In this work, we propose a novel SQL optimizer that strikes a balance between query runtime performance and private information exposure. Our approach to ensuring that the access control policies regulating data disclosure are enforced during distributed query execution is based upon a state-of-the-art authorization model from the literature and a preference-aware query optimizer. Our preliminary studies show that our approach outperforms the way the authorization model was originally implemented in terms of query runtime performance which is crucial for the operation on Big Data. To improve it, we ad- just the algorithms utilized by a preference-aware query optimizer.

Keywords: Big data, Distributed databases, Query optimization, Access model, Privacy

Published In: The 34th ACM/SIGAPP Symposium On Applied Computing: Special Track on Databases and Big Data Management (DBDM)

Pages: 1-8

Year Published: 2019

Project: PAQO Subject Area: Data Privacy, Query Processing

Publication Type: Conference Paper

Sponsor: NSF CNS-1704139, NSF CNS-1253204, NSF CPS-1739413, NIH U01HL137159

Citation:Text Latex BibTex XML Ekaterina B. Dimitrova, Panos K. Chrysanthis, and Adam J. Lee. Authorization-Aware Optimization for Multi-Provider Queries. The 34th ACM/SIGAPP Symposium On Applied Computing: Special Track on Databases and Big Data Management (DBDM). 1-8. 2019.