کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
430370 687969 2011 23 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Privacy Preserving OLAP over Distributed XML Data: A Theoretically-Sound Secure-Multiparty-Computation Approach
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Privacy Preserving OLAP over Distributed XML Data: A Theoretically-Sound Secure-Multiparty-Computation Approach
چکیده انگلیسی

Privacy Preserving Distributed OLAP is becoming a critical challenge for next-generation Business Intelligence (BI) scenarios, due to the “natural suitability” of OLAP in analyzing distributed massive BI repositories in a multidimensional and multi-granularity manner. In particular, in these scenarios XML-formatted BI repositories play a dominant role, due to the well-know amenities of XML in modeling and representing distributed business data. However, while Privacy Preserving Distributed Data Mining has been widely investigated, the problem of effectively and efficiently supporting privacy preserving OLAP over distributed collections of XML documents, which is relevant in practice, has been neglected so far. In order to fulfill this gap, we propose a novel Secure Multiparty Computation (SMC)-based privacy preserving OLAP framework for distributed collections of XML documents. The framework has many novel features ranging from nice theoretical properties to an effective and efficient protocol, called Secure Distributed OLAP aggregation protocol (SDO). The efficiency of our approach has been validated by an experimental evaluation over distributed collections of synthetic, benchmark and real-life XML documents.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computer and System Sciences - Volume 77, Issue 6, November 2011, Pages 965-987