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Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications (Advances in Information Security, Band 68) - Softcover
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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.
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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 interestedin privacy, algorithms, or web applications.
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Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications (Advances in Information Security, 68)
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Preserving Privacy Against Side-Channel Leaks : From Data Publishing to Web Applications
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Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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. Artikel-Nr. 29628265/2
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Preserving Privacy Against Side-Channel Leaks | From Data Publishing to Web Applications
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Taschenbuch. Zustand: Neu. Preserving Privacy Against Side-Channel Leaks | From Data Publishing to Web Applications | Wen Ming Liu (u. a.) | Taschenbuch | Advances in Information Security | xiii | Englisch | 2018 | Springer | EAN 9783319826264 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 114226929
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Preserving Privacy Against Side-Channel Leaks : From Data Publishing to Web Applications
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Artikel-Nr. 9783319826264
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