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Data warehouses contain sensitive data that must be secured in two ways: by defining appropriate access rights to the users and by preventing potential data inferences. Inspired from development methods for information systems, the first way of securing a data warehouse has been treated in the literature during the early phases of the development cycle. However, despite the high risks of inferences, the second way is not sufficiently taken into account in the design phase; it is rather left to the administrator of the data warehouse. However, managing inferences during the exploitation phase may induce high maintenance costs and complex OLAP server administration. In this paper, we propose an approach that, starting from the conceptual model of the data sources, assists the designer of the data warehouse in indentifying
multidimensional sensitive data and those that may be subject to inferences.