Secure Data Management 7th VLDB Workshop, SDM 2010, Singapore, September 17, 2010, Proceedings /

The VLDB Secure Data Management Workshop was held for the 7th time this year. The topic of data security remains an important area of research especially due to the growing proliferation of data in open environments as a result of emerging data services such as cloud computing, location based servic...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Jonker, Willem (Editor ), Petkovic, Milan (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Information Systems and Applications, incl. Internet/Web, and HCI ; 6358
Temas:
Cryptography.
Data encryption (Computer science).
Data structures (Computer science).
Information theory.
Computer networks .
Application software.
Electronic data processing-Management.
Computers and civilization.
Cryptology.
Data Structures and Information Theory.
Computer Communication Networks.
Computer and Information Systems Applications.
IT Operations.
Computers and Society.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Keynote Paper
  • Assuring Data Trustworthiness - Concepts and Research Challenges
  • Privacy Protection
  • On-the-Fly Hierarchies for Numerical Attributes in Data Anonymization
  • eM2: An Efficient Member Migration Algorithm for Ensuring k-Anonymity and Mitigating Information Loss
  • Constrained Anonymization of Production Data: A Constraint Satisfaction Problem Approach
  • Privacy Preserving Event Driven Integration for Interoperating Social and Health Systems
  • Data Security in Open Environments
  • Joining Privately on Outsourced Data
  • Computationally Efficient Searchable Symmetric Encryption
  • Towards the Secure Modelling of OLAP Users' Behaviour
  • A Formal P3P Semantics for Composite Services
  • A Geometric Approach for Efficient Licenses Validation in DRM
  • Differentially Private Data Release through Multidimensional Partitioning.

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