Login | Register

Service-Oriented Architecture for High-Dimensional Private Data Mashup


Service-Oriented Architecture for High-Dimensional Private Data Mashup

Fung, Benjamin C.M., Trojer, Thomas, Hung, Patrick C.K., Xiong, Li, Al-Hussaeni, Khalil and Dssouli, Rachida (2012) Service-Oriented Architecture for High-Dimensional Private Data Mashup. IEEE Transactions on Services Computing, 5 (3). pp. 373-386. ISSN 1939-1374

[thumbnail of service_oriented_architecture.pdf]
Text (application/pdf)
service_oriented_architecture.pdf - Accepted Version

Official URL: http://dx.doi.org/10.1109/TSC.2011.13


Mashup is a web technology that allows different service providers to flexibly integrate their expertise and to deliver highly customizable services to their customers. Data mashup is a special type of mashup application that aims at integrating data from multiple data providers depending on the user's request. However, integrating data from multiple sources brings about three challenges: 1) Simply joining multiple private data sets together would reveal the sensitive information to the other data providers. 2) The integrated (mashup) data could potentially sharpen the identification of individuals and, therefore, reveal their person-specific sensitive information that was not available before the mashup. 3) The mashup data from multiple sources often contain many data attributes. When enforcing a traditional privacy model, such as K-anonymity, the high-dimensional data would suffer from the problem known as the curse of high dimensionality, resulting in useless data for further data analysis. In this paper, we study and resolve a privacy problem in a real-life mashup application for the online advertising industry in social networks, and propose a service-oriented architecture along with a privacy-preserving data mashup algorithm to address the aforementioned challenges. Experiments on real-life data suggest that our proposed architecture and algorithm is effective for simultaneously preserving both privacy and information utility on the mashup data. To the best of our knowledge, this is the first work that integrates high-dimensional data for mashup service.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering
Item Type:Article
Authors:Fung, Benjamin C.M. and Trojer, Thomas and Hung, Patrick C.K. and Xiong, Li and Al-Hussaeni, Khalil and Dssouli, Rachida
Journal or Publication:IEEE Transactions on Services Computing
Digital Object Identifier (DOI):10.1109/TSC.2011.13
ID Code:974921
Deposited On:30 Oct 2012 16:04
Last Modified:18 Jan 2018 17:39
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top