First, the sensitive data stored in underlying data warehouses must be kept secret. Preserving Privacy for On-Line Analytical Processing addresses the privacy issue of On-Line Analytic Processing (OLAP) systems. Second, analytical queries about the data must be allowed for decision support purposes. This volume reviews a series of methods that can precisely answer data cube-style OLAP, regarding sensitive data while provably preventing adversaries from inferring data. OLAP systems usually need to meet two conflicting goals. The main challenge is that sensitive data can be inferred from answers to seemingly innocent aggregations of the data. Preserving Privacy for On-Line Analytical Processing is appropriate for practitioners in industry as well as graduate-level students in computer science and engineering.
Books > Computer Science
Preserving Privacy In On-Line Analytical Processing (OLAP)
Specifications of Preserving Privacy In On-Line Analytical Processing (OLAP) | |
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Category | Medien > Bücher |
Instock | instock |