Privacy-preservation in the integration and querying of multidimensional data models
Michael Mireku Kwakye, Ken E. Barker · 2016
The process of integrating instances of disparate data sources to generate an enterprise-wide data warehouse requires identifying related fact and dimension table attributes. The ability to process privacy-aware user-centric queries across these disparate, but related, multidimensional data items within the framework of a Single Consolidated Data Warehouse (SCDW) poses a much more important challenge. In this paper, we propose a privacy methodology that encapsulates the SCDW and provides privacy protection to the underlying data sources at different user-specifiable levels during query processing. This methodology provides protection from various attack models inherent in its framework architecture. Additionally, the methodology offers efficient privacy-aware query processing on the integrated data warehouse.