Preserving Privacy Against Side-Channel Leaks

From Data Publishing to Web Applications

  • Wen Ming Liu
  • Lingyu Wang

Part of the Advances in Information Security book series (ADIS, volume 68)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Wen Ming Liu, Lingyu Wang
    Pages 1-6
  3. Wen Ming Liu, Lingyu Wang
    Pages 7-16
  4. Wen Ming Liu, Lingyu Wang
    Pages 71-97
  5. Wen Ming Liu, Lingyu Wang
    Pages 133-142

About this book


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.


Data privacy Data publishing Privacy preservation Side-channel attack Public algorithm k-Anonymity I-Diversity Traffic padding Web application Smart metering

Authors and affiliations

  • Wen Ming Liu
    • 1
  • Lingyu Wang
    • 2
  1. 1.Concordia Institute for Information Systems EngineeringConcordia UniversityMontrealCanada
  2. 2.Concordia Institute for Information Systems EngineeringConcordia UniversityMontrealCanada

Bibliographic information

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