Overview
- This book covers (including exercises and examples) many of the fundamental, widely known PETs (Privacy Enhancing Technologies), as well as some of the important emerging technologies in this field
- Targets primarily graduate students (and upper-year undergraduate students) in computer science, software engineering, mathematics, or related fields, who have an interest in algorithms and technologies that can be used to protect privacy in online environments
- This is the only textbook that presents a general introduction to PETs
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Table of contents (12 chapters)
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Front Matter
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Supplemental Chapters
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Front Matter
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Back Matter
Keywords
- Privacy
- security
- privacy enhancing technologies (PETs)
- personally identifiable information (PII)
- cryptography
- k-anonymity
- pseudonymity
- privacy policies
- Privacy in machine learning
- P3P
- Hippocratic databases
- Differential privacy
- Multi-party computation (MPC)
- Attribute-based encryption (ABE)
- Credential systems
- Off-the-Record (OTR) messaging
- Information Retrieval (PIR)
- SSL/TLS for privacy
- Onion routing
- Tor
About this book
Why is privacy important? How and why is your privacy being eroded and what risks can this pose for you? What are some tools for protecting your privacy in online environments? How can these tools be understood, compared, and evaluated? What steps can you take to gain more control over your personal data?
This book addresses the above questions by focusing on three fundamental elements:
- It introduces a simple classification of PETs that allows their similarities and differences to be highlighted and analyzed;
- It describes several specific PETs in each class, including both foundational technologies and important recent additions to the field;
- It explainshow to use this classification to determine which privacy goals are actually achievable in a given real-world environment. Once the goals are known, this allows the most appropriate PETs to be selected in order to add the desired privacy protection to the target environment. To illustrate, the book examines the use of PETs in conjunction with various security technologies, with the legal infrastructure, and with communication and computing technologies such as Software Defined Networking (SDN) and Machine Learning (ML).
Designed as an introductory textbook on PETs, this book is essential reading for graduate-level students in computer science and related fields, prospective PETs researchers, privacy advocates, and anyone interested in technologies to protect privacy in online environments.
Authors and Affiliations
About the author
Dr. Adams has maintained a long-standing interest in the creation of effective techniques to preserve and enhance privacy on the Internet. His contributions in this area include techniques to add delegation, non-transferability, and multi-show to Digital Credentials, architectures to enforce privacy in web-browsing environments, and mechanisms to add privacy to location-based services and blockchains. He was Co-Chair of the international conference Selected Areas in Cryptography (1997, 1999, 2007, and 2017), and was General Chair of the 7th International Privacy Enhancing Technologies Symposium (2007).
He lives in Ottawa with his wife and children and enjoys music, good food, and classic movies (old and new).
Bibliographic Information
Book Title: Introduction to Privacy Enhancing Technologies
Book Subtitle: A Classification-Based Approach to Understanding PETs
Authors: Carlisle Adams
DOI: https://doi.org/10.1007/978-3-030-81043-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-81042-9Published: 31 October 2021
eBook ISBN: 978-3-030-81043-6Published: 30 October 2021
Edition Number: 1
Number of Pages: XIII, 324
Number of Illustrations: 7 b/w illustrations, 14 illustrations in colour
Topics: Privacy, Cryptology, Mobile and Network Security, Systems and Data Security