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PAIRSE: a privacy-preserving service-oriented data integration system

Published: 17 October 2013 Publication History

Abstract

Privacy is among the key challenges to data integration in many sectors, including healthcare, e-government, etc. The PAIRSE project aims at providing a flexible, looselycoupled and privacy-preserving data integration system in P2P environments. The project exploits recent Web standards and technologies such asWeb services and ontologies to export data from autonomous data providers as reusable services, and proposes the use of service composition as a viable solution to answer data integration needs on the fly. The project proposed new composition algorithms and service/composition execution models that preserve privacy of data manipulated by services and compositions. The proposed integration system was demonstrated at EDBT 2013 and VLDB 2011.

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Published In

cover image ACM SIGMOD Record
ACM SIGMOD Record  Volume 42, Issue 3
September 2013
69 pages
ISSN:0163-5808
DOI:10.1145/2536669
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2013
Published in SIGMOD Volume 42, Issue 3

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  • (2022)Obscure: Information-Theoretically Secure, Oblivious, and Verifiable Aggregation Queries on Secret-Shared Outsourced DataIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.298393234:2(843-864)Online publication date: 1-Feb-2022
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