Privacy Preserving OLAP over Distributed XML Documents
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.
XML, competitive intelligence, data mining, data privacy
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