Privacy-preserving data mashup

Abstract : Data Mashup is a special class of mashup application that combines information on the fly from multiple data sources to respond to transient business needs. Mashing up data requires an important programming skill on the side of mashups' creators, and involves handling many challenging privacy and security concerns raised by data providers. This situation prevents non-expert users from mashing up data at large. In this paper, we propose a declarative approach for mashing-up data. The approach allows data mashup creators to create data mashups without any programming involved, they just need to specify "declaratively" their data needs. The approach will then build the mashups automatically while taking into account the data's privacy and security concerns
Document type :
Conference papers
Complete list of metadatas

Cited literature [15 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01301935
Contributor : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Submitted on : Wednesday, April 13, 2016 - 12:21:55 PM
Last modification on : Tuesday, February 26, 2019 - 11:27:11 AM
Long-term archiving on : Tuesday, November 15, 2016 - 2:31:11 AM

File

AINA_2011_Barhamgi.pdf
Files produced by the author(s)

Identifiers

Citation

Mahmoud Barhamgi, Djamal Benslimane, Chirine Ghedira, Alda Lopes Gancarski. Privacy-preserving data mashup. AINA 2011 : 25th IEEE International Conference on Advanced Information Networking and Applications, Mar 2011, Biopolis, Singapore. pp.467 - 474, ⟨10.1109/AINA.2011.47 ⟩. ⟨hal-01301935⟩

Share

Metrics

Record views

400

Files downloads

148