
Preserving Privacy Against Side-Channel Leaks
From Data Publishing to Web Applications
Springer (Publisher)
Published on 19. October 2016
Book
Hardback
XIII, 142 pages
978-3-319-42642-6 (ISBN)
Description
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 strategy independent of data utility measures and syntactic privacy properties before discussing an extended approach to improve the efficiency. Next, the book explores privacy-preserving traffic padding in Web applications, first via a model to quantify privacy and cost and then by introducing randomness to provide background knowledge-resistant privacy guarantee. Finally, the book considers privacy-preserving smart metering by proposing a light-weight approach to simultaneously preserving users' privacy and ensuring billing accuracy. Designed for researchers and professionals, this book is also suitable for advanced-level students interested in privacy, algorithms, or web applications.
More details
Series
Edition
1st ed. 2016
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
18 s/w Abbildungen, 1 farbige Abbildung
XIII, 142 p. 19 illus., 1 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 15 mm
Weight
407 gr
ISBN-13
978-3-319-42642-6 (9783319426426)
DOI
10.1007/978-3-319-42644-0
Schweitzer Classification
Other editions
Additional editions

Wen Ming Liu | Lingyu Wang
Preserving Privacy Against Side-Channel Leaks
From Data Publishing to Web Applications
Book
04/2018
Springer
€106.99
Shipment within 10-15 days

Wen Ming Liu | Lingyu Wang
Preserving Privacy Against Side-Channel Leaks
From Data Publishing to Web Applications
E-Book
08/2016
1st Edition
Springer
€96.29
Available for download
Content
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.