ENGLISH

Preserving privacy in on-line analytical processing (OLAP)

By Wang , Sushil , Lingyu;Jajodia

Book information

Publisher
Springer
ISBN
9780387462738, 9780387327235, 9780387327204, 0387276343, 0387290168, 0387302360, 0387341897, 0387462732, 9780387462745, 0387462740
Language
english
Format
PDF
Filesize
58 MB (61181934 bytes)
Series
Advances in information security [29]
Pages
180\396
Time added
2020-11-29 04:22:03

Description

Preserving Privacy for On-Line Analytical Processingaddresses the privacy issue of On-Line Analytic Processing (OLAP) systems. OLAP systems usually need to meet two conflicting goals. First, the sensitive data stored in underlying data warehouses must be kept secret. Second, analytical queries about the data must be allowed for decision support purposes. The main challenge is that sensitive data can be inferred from answers to seemingly innocent aggregations of the data. 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. Preserving Privacy for On-Line Analytical Processingis appropriate for practitioners in industry as well as graduate-level students in computer science and engineering.

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