Mashup is a web technology that combines information from more than one source into a single web application. This technique provides a new platform for different data providers to flexibly integrate their expertise and deliver highly customizable services to their customers. Nonetheless, combining data from different sources could potentially reveal person-specific sensitive information. In this paper, we study and resolve a real-life privacy problem in a data mashup application for the financial industry in Sweden. Therefore we propose a service-oriented architecture for privacy-preserving data mashup together with a multiparty protocol to securely integrate private data from different data providers, whereas the integrated data still retains the essential information for supporting general data exploration or a specific data mining task, such as classification analysis. Experiments on real-life data suggest that our proposed method is effective for simultaneously preserving both privacy and information usefulness.
展开▼
