Preserving Privacy Against Side-Channel Leaks - From Data Publishing to Web Applications (Paperback, Softcover reprint of the original 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Advances in Information Security, 68
Release date:	April 2018
First published:	2016
Authors:	Wen Ming Liu • Lingyu Wang
Dimensions:	235 x 155 x 9mm (L x W x T)
Format:	Paperback
Pages:	142
Edition:	Softcover reprint of the original 1st ed. 2016
ISBN-13:	978-3-319-82626-4
Categories:	Books > Reference & Interdisciplinary > Communication studies > Coding theory & cryptology Books > Computing & IT > Computer communications & networking > Network security Books > Computing & IT > Internet > Network computers
LSN:	3-319-82626-3
Barcode:	9783319826264

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