We introduce a novel Privacy Preserving Distributed Data Mining routine over collections of XML documents stored in distributed environments, called secure distributed OLAP aggregation, which plays a critical role in next-generation distributed Business Intelligence (BI) scenarios. In order to effectively and efficiently support secure distributed OLAP aggregation routines in such scenarios, a privacy preserving distributed OLAP framework that embeds several points of innovation in the context of privacy preserving OLAP research is hence proposed and deeply investigated in this paper.
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