Preserving Privacy Against Side-channel Leaks: From Data Publishing to Web Applications: 68 - Rilegato

Liu, Wen Ming; Wang, Lingyu

Rilegato

ISBN 10: 3319426427 ISBN 13: 9783319426426

Casa editrice: Springer-Verlag New York Inc, 2016

Riassunto

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.

Su questo libro

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer-Verlag New York Inc
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 3319426427
• ISBN 13: 9783319426426
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 156
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania