Skip to main content
  • Book
  • © 2016

Preserving Privacy Against Side-Channel Leaks

From Data Publishing to Web Applications

  • Provides readers with insights into three important data privacy domains: data publishing, Web application, and smart metering
  • Presents the similarities between seemingly different side-channels attacks in various domains
  • Reveals promising future directions towards generic privacy solutions that are resistant to side channel attacks
  • Includes supplementary material: sn.pub/extras

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

  • 4160 Accesses

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiii
  2. Introduction

    • Wen Ming Liu, Lingyu Wang
    Pages 1-6
  3. Related Work

    • Wen Ming Liu, Lingyu Wang
    Pages 7-16
  4. Web Applications: k-Indistinguishable Traffic Padding

    • Wen Ming Liu, Lingyu Wang
    Pages 71-97
  5. The Big Picture: A Generic Model of Side-Channel Leaks

    • 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.


Authors and Affiliations

  • Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada

    Wen Ming Liu, Lingyu Wang

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access