PPPDM- A Privacy-Preserving Platform for Data Mashup

Mahmoud Barhamgi 1 Djamal Benslimane 1 Chirine Ghedira 1 Benharkat Aïcha-Nabila 1
1 SOC - Service Oriented Computing
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : The rapidly evolving nature of business requirements in current markets calls for a newtype of applications that is able to follow and respond rapidly to these changing requirements. Thistype of applications is known as the ”Situational Applications”, i.e., the applications that cometogether for solving some immediate business problems. Data Mashup is an important class of thesituational applications that combines information on the fly from multiple data sources to respond toimmediate business data needs. Mashing up data requires important programming skills on the sideof mashups’ creators, and involves handling many challenging privacy and security concerns raisedby data providers. In general, this situation prevents the non expert users from building their desiredmashups on their own. In this paper, we propose a declarative approach for mashing-up data. In ourproposed approach, data sources are exported as Web services and described as RDF views overdomain ontologies to formally define their semantics. The approach allows the mashup’s creators tocreate data mashups without any programming involved, they just need to specify “declaratively”their data needs. The approach exploits the mature query rewriting techniques to build the mashupsautomatically while taking into account the data’s privacy and security concerns. We apply theproposed approach to the healthcare domain, and report a thorough experimental evaluation. Thereported results are very promising.
Document type :
Journal articles
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https://hal.archives-ouvertes.fr/hal-01352950
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Submitted on : Wednesday, August 10, 2016 - 4:16:28 PM
Last modification on : Monday, December 10, 2018 - 5:50:38 PM

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  • HAL Id : hal-01352950, version 1

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Mahmoud Barhamgi, Djamal Benslimane, Chirine Ghedira, Benharkat Aïcha-Nabila. PPPDM- A Privacy-Preserving Platform for Data Mashup. International Journal of Grid and Utility Computing, Inderscience, 2012, 2/3, 3, pp.175-187. ⟨hal-01352950⟩

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