Preserving Privacy in On-Line Analytical Processing (Olap)
- Indbinding:
- Hardback
- Sideantal:
- 180
- Udgivet:
- 14. november 2006
- Udgave:
- 2007
- Størrelse:
- 161x16x242 mm.
- Vægt:
- 445 g.
- 8-11 hverdage.
- 7. december 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Preserving Privacy in On-Line Analytical Processing (Olap)
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.
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.
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Bogen Preserving Privacy in On-Line Analytical Processing (Olap) findes i følgende kategorier:
- Business og læring > Computer og IT
- Sprog og lingvistik
- Reference, information og tværfaglige emner > Forskning og information: generelt > Informationsteori
- Reference, information og tværfaglige emner > Forskning og information: generelt > Kodeteori og kryptologi
- Databehandling og informationsteknologi > Programmering / softwareudvikling > Algoritmer og datastrukturer
- Databehandling og informationsteknologi > Databaser
- Databehandling og informationsteknologi > Datasikkerhed > Datakryptering
- Databehandling og informationsteknologi > Anvendt databehandling
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