Carlisle Adams - Introduction to Privacy Enhancing Technologies: A Classification-Based Approach to Understanding PETs

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This book has been refined and developed in a graduate course that I have taught 15 times at the University of Ottawa since 2004; the classification -based approach that it uses was first published as a research paper in 2006. Like a number of my colleagues around the world, I have for a long time been somewhat frustrated by the absence of a textbook on PETs that I could use for my course. While it is appropriate and reasonable in a graduate course to point students to a set of foundational and recent academic papers on the topic of discussion, I have nevertheless felt that it would be useful to have a single text that can serve as a general introduction to the field. Eventually, since no one else seemed to be doing this (and with the unexpected coincidence of a sabbatical year and a global pandemic removing all other options for things to distract me!), I decided to put this book together.

Consequently, the primary target audience of this book is graduate and upper-year undergraduate students in computer science and software engineering with an interest in technologies that protect and enhance privacy in online environments. However, my hope is that students, researchers, practitioners, and interested parties in many other fields and at many different levels will find this book instructive and helpful. Although privacy is a much bigger field than just PETs, privacy advocates in all areas can benefit from understanding the role that PETs can play in guarding some aspects of privacy in our online interactions.

In terms of organization, I feel that it is essential to begin with the first two chapters, which motivate the need for PETs and describe the classification -based approach that this book uses (the privacytree ). The six subsequent chapters (on various example PETs in each of the six leaves of the tree) are mostly standalone and can be read in any order. Chapter valuable: this chapter collects together all the references at the end of the individual chapters throughout the book, adds a hyperlink to each reference (for easy retrieval), and provides a (short) bibliography of recommended reading in privacy.

I would like to greatly acknowledge the academic system in which we operate: without a year-long sabbatical in which to focus, it would have been far more difficult to complete this book in a reasonable time! I am extremely grateful, too, for the comments and feedback I received from several reviewers on an initial draft of this manuscript; my many thanks go to Mozhgan Nasr Azadani, Ian Goldberg, Marion Rodrigues, and Paul Syverson. Their careful reading and attention to detail significantly improved the clarity, coverage, and correctness of the text in many places. (But note, of course, that any errors remaining in the book are entirely due to the author, not the reviewers!) Finally, I would like to thank the many friends and relatives who encouraged and supported me in this project, as well as Susan Lagerstrom-Fife and the terrific team at Springer who brought this book to publication with dedication, efficiency, and professionalism.