Springer
Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications
Product Code:
9783319426426
ISBN13:
9783319426426
Condition:
New
$118.37
Preserving Privacy Against Side-Channel Leaks: From Data Publishing to Web Applications
$118.37
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.
| Author: Wen Ming Liu |
| Publisher: Springer |
| Publication Date: Oct 19, 2016 |
| Number of Pages: 142 pages |
| Binding: Hardback or Cased Book |
| ISBN-10: 3319426427 |
| ISBN-13: 9783319426426 |
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