Articoli correlati a Preserving Privacy in On-Line Analytical Processing...

Preserving Privacy in On-Line Analytical Processing (OLAP): 29 - Rilegato

Libro 21 di 109: Advances in Information Security

Wang, Lingyu; Jajodia, Sushil; Wijesekera, Duminda

 
9780387462738: Preserving Privacy in On-Line Analytical Processing (OLAP): 29
Rilegato
ISBN 10: 0387462732 ISBN 13: 9780387462738
Casa editrice: Springer-Verlag GmbH, 2006

Sinossi

Preserving Privacy for On-Line Analytical Processing addresses 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 Processing is appropriate for practitioners in industry as well as graduate-level students in computer science and engineering.

 

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

On-Line Analytic Processing (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. Existing inference control methods in statistical databases usually exhibit high performance overhead and limited effectiveness when applied to OLAP systems.

Preserving Privacy in On-Line Analytical Processing reviews a series of methods that can precisely answer data cube-style OLAP queries regarding sensitive data while provably preventing adversaries from inferring the data. How to keep the performance overhead of these security methods at a reasonable level is also addressed. Achieving a balance between security, availability, and performance is shown to be feasible in OLAP systems.

Preserving Privacy in On-Line Analytical Processing is designed for the professional market, composed of practitioners and researchers in industry.  This book is also appropriate for graduate-level students in computer science and engineering.

 

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer-Verlag GmbH
Data di pubblicazione
2006
Lingua
Inglese
ISBN 10 
0387462732
ISBN 13 
9780387462738
Rilegatura
Copertina rigida
Numero di pagine
198
Contatto del produttore
non disponibile
Persona responsabile
gpsr@libri.de
gpsr@libri.de

Europaallee 1
Bad Hersfeld
36244
Germania