<DIV>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.&NBSP;</DIV><DIV>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.&NBSP;</DIV><DIV>DESIGNED FOR RESEARCHERS AND PROFESSIONALS, THIS BOOK IS ALSO SUITABLE FOR ADVANCED-LEVEL STUDENTS INTERESTED IN PRIVACY, ALGORITHMS, OR WEB APPLICATIONS.</DIV><DIV><BR></DIV>
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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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Buch. 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. 9783319426426
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