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

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Preserving Privacy Against Side-Channel Leaks/ by Wen Ming Liu, Lingyu Wang.
Reminder of title:	From Data Publishing to Web Applications /
Author:	Liu, Wen Ming.
other author:	Wang, Lingyu.
Description:	XIII, 142 p. 19 illus., 1 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computer security. -
Online resource:	https://doi.org/10.1007/978-3-319-42644-0
ISBN:	9783319426440

Preserving Privacy Against Side-Channel Leaks = From Data Publishing to Web Applications /
Liu, Wen Ming.

Preserving Privacy Against Side-Channel LeaksFrom Data Publishing to Web Applications /[electronic resource] :by Wen Ming Liu, Lingyu Wang. - 1st ed. 2016. - XIII, 142 p. 19 illus., 1 illus. in color.online resource. - Advances in Information Security,681568-2633 ;. - Advances in Information Security,.

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.

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.

ISBN: 9783319426440

Standard No.: 10.1007/978-3-319-42644-0doiSubjects--Topical Terms:

557122
Computer security.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

Preserving Privacy Against Side-Channel Leaks = From Data Publishing to Web Applications /
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520 $a 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.
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