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

This textbook offers a comprehensive guide to Privacy Enhancing Technologies (PETs), explaining their importance, risks, and tools for protecting privacy in online environments. It introduces a classification of PETs and discusses specific technologies within each class, highlighting their capabilities and limitations. By utilizing this classification, readers can determine which PETs are most suitable for achieving their privacy goals in various real-world scenarios. The book also explores the integration of PETs with security technologies, legal infrastructure, and communication and computing technologies such as SDN and ML. It is designed as an introductory textbook for graduate-level students, researchers, privacy advocates, and anyone interested in technologies for protecting privacy in online environments.

Format: Paperback / softback
Length: 324 pages
Publication date: 31 October 2021
Publisher: Springer Nature Switzerland AG

This comprehensive textbook offers a unique perspective on the vast array of Privacy Enhancing Technologies (PETs) currently available. By providing clear and detailed explanations, it addresses key privacy-centered concerns and sheds light on the erosion of privacy in online environments. It explores the importance of privacy, the risks associated with its erosion, and the tools available to protect personal data in online environments.

The book adopts a systematic approach, categorizing PETs into three fundamental elements:

Classification of PETs: This section introduces a simple classification system that facilitates the identification of similarities and differences among PETs. It helps readers understand the broader landscape of privacy protection technologies and enables them to make informed decisions about which PETs are most suitable for specific privacy goals.

Specific PETs: Each category is further explored with detailed descriptions of several specific PETs, including both foundational technologies and important recent additions to the field. This section provides a deep understanding of the capabilities and limitations of each technology, enabling readers to select the most appropriate PETs for their specific needs.

Application of Classification: The book demonstrates how to use the classification system to determine which privacy goals are achievable in a given real-world environment. By identifying the appropriate PETs, readers can implement effective privacy protection measures to safeguard their personal data and ensure the confidentiality of their online activities.

To illustrate the practical application of PETs, the book examines their use in conjunction with various security technologies, legal infrastructure, and communication and computing technologies such as Software Defined Networking (SDN) and Machine Learning (ML). This interdisciplinary approach provides a comprehensive understanding of how PETs can be integrated into existing systems and networks to enhance privacy protection.

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. Its comprehensive coverage, clear explanations, and practical examples make it a valuable resource for anyone seeking to gain a deeper understanding of privacy enhancing technologies and their role in shaping the future of digital privacy.

Weight: 522g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030810429
Edition number: 1st ed. 2021