Separation of Duties for Multiple Relations in Cloud Databases as an Optimization Problem

Abstract

Confidentiality concerns are important in the context of cloud databases. In this paper, the technique of vertical fragmentation is explored to break sensitive associations between columns of several database tables according to confidentiality constraints. By storing insensitive portions of the database at different non-communicating servers it is possible to overcome confidentiality concerns. In addition, visibility constraints and data dependencies are supported. Moreover, to provide some control over the distribution of columns among different servers, novel closeness constraints are introduced. Finding confidentiality-preserving fragmentations is studied in the context of mathematical optimization and a corresponding integer linear program formulation is presented. Benchmarks were performed to evaluate the suitability of our approach.