Secure Data Management (eBook, PDF)

5th VLDB Workshop, SDM 2008, Auckland, New Zealand, August 24, 2008, Proceedings
Redaktion: Jonker, Willem; Petkovic, Milan

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 5th VLDB Workshop on Secure Data Management, SDM 2008, held in Auckland, New Zealand, on August 24, 2008, in conjunction with VLDB 2008.

The 11 revised full papers presented together with a keynote paper were carefully reviewed and selected from 32 submissions for publication in the book. The papers are organized in topical sections on database security, trust management, privacy protection, and security and privacy in healthcare. The volume is rounded off by 3 position papers whose topics range from data disclosure control, via privacy protection to access control.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 229
• Erscheinungstermin: 18. August 2008
• Englisch
• ISBN-13: 9783540852599
• Artikelnr.: 44222549

Inhaltsangabe

Invited Keynote Paper.
How Anonymous Is k
Anonymous? Look at Your Quasi
ID.
Database Security.
Simulatable Binding: Beyond Simulatable Auditing.
ARUBA: A Risk
Utility
Based Algorithm for Data Disclosure.
Responding to Anomalous Database Requests.
Auditing Inference Based Disclosures in Dynamic Databases.
Trust Management.
An Approach to Evaluate Data Trustworthiness Based on Data Provenance.
Exploiting Preferences for Minimal Credential Disclosure in Policy
Driven Trust Negotiations.
A Trusted Approach to E
Commerce.
Privacy Protection.
A Game
Theoretical Approach to Data
Privacy Protection from Context
Based Inference Attacks: A Location
Privacy Protection Case Study.
Query Rewriting for Access Control on Semantic Web.
Security and Privacy in Healthcare.
On the Facilitation of Fine
Grained Access to Distributed Healthcare Data.
A Type
and
Identity
Based Proxy Re
encryption Scheme and Its Application in Healthcare.
Position Papers.
A Methodology for Bridging between RBAC and an Arbitrary Application Program.
An Anonymity Model Achievable Via Microaggregation.
Engineering Privacy Requirements in Business Intelligence Applications.