Preserving Privacy Against Side-Channel Leaks From Data Publishing to Web Applications /

This book offers a novel approach to data privacy by unifying side-channel attacks within a general conceptual framework. This book then applies the framework in three concrete domains. First, the book examines privacy-preserving data publishing with publicly-known algorithms, studying a generic str...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Liu, Wen Ming (Autor), Wang, Lingyu (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Advances in Information Security, 68
Temas:
Data protection.
Cryptography.
Data encryption (Computer science).
Computer networks .
Data and Information Security.
Cryptology.
Computer Communication Networks.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction
  • Related Work
  • Data Publishing: Trading off Privacy with Utility through the k-Jump Strategy
  • Data Publishing: A Two-Stage Approach to Improving Algorithm Efficiency
  • Web Applications: k-Indistinguishable Traffic Padding
  • Web Applications: Background-Knowledge Resistant Random Padding
  • Smart Metering: Inferences of Appliance Status from Fine-Grained Readings
  • The Big Picture: A Generic Model of Side-Channel Leaks
  • Conclusion.

Ejemplares similares