Preserving Privacy Against Side-Channel Leaks

From Data Publishing to Web Applications

Wen Ming Liu, Lingyu Wang (Autoren)

Buch | Softcover

XIII, 142 Seiten

2018 | 1. Softcover reprint of the original 1st ed. 2016
Springer International Publishing (Verlag)
978-3-319-82626-4 (ISBN)

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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.

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.

Erscheinungsdatum	20.07.2018
Reihe/Serie	Advances in Information Security
Zusatzinfo	XIII, 142 p. 19 illus., 1 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	2467 g
Themenwelt	Informatik ► Netzwerke ► Sicherheit / Firewall
Themenwelt	Informatik ► Theorie / Studium ► Kryptologie
Schlagworte	data privacy • data publishing • I-Diversity • K-anonymity • privacy preservation • Public algorithm • side-channel attack • Smart Metering • Traffic padding • Web application
ISBN-10	3-319-82626-3 / 3319826263
ISBN-13	978-3-319-82626-4 / 9783319826264
Zustand	Neuware