Preserving Privacy Against Side-Channel Leaks
Autor: | Wen Ming Liu, Lingyu Wang |
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EAN: | 9783319426440 |
eBook Format: | |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 24.08.2016 |
Untertitel: | From Data Publishing to Web Applications |
Kategorie: | |
Schlagworte: | Data privacy;Data publishing;Privacy preservation;Side-channel attack;Public algorithm;k-Anonymity;I-Diversity;Traffic padding;Web application;Smart metering |
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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.