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

by Lingyu Wang and Wen Ming Liu

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.

• Format: Paperback
• Language: English
• ISBN: 3319826263
• ISBN13: 9783319826264
• Release Date: April 2018
• Publisher: Springer
• Length: 142 Pages
• Weight: 0.51 lbs.
• Dimensions: 0.3" x 6.1" x 9.2"