Overview
- Presents the main privacy models and the main technologies
- Describes some of the most relevant algorithms
- Offers characterization, comparison, and examples of privacy models
Part of the book series: Undergraduate Topics in Computer Science (UTICS)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Privacy technologies clearly are needed for ensuring that data does not lead to disclosure, but also that statistics or even data-driven machine learning models do not lead to disclosure. For example, can a deep-learning model be attacked to discover that sensitive data has been used for its training? This accessible textbook presents privacy models, computational definitions of privacy, and methods to implement them. Additionally, the book explains and gives plentiful examples of how to implement—among other models—differential privacy, k-anonymity, and secure multiparty computation.
Topics and features:
- Provides integrated presentation of data privacy (including tools from statistical disclosure control, privacy-preserving data mining, and privacy for communications)
- Discusses privacy requirements and tools fordifferent types of scenarios, including privacy for data, for computations, and for users
- Offers characterization of privacy models, comparing their differences, advantages, and disadvantages
- Describes some of the most relevant algorithms to implement privacy models
- Includes examples of data protection mechanisms
This unique textbook/guide contains numerous examples and succinctly and comprehensively gathers the relevant information. As such, it will be eminently suitable for undergraduate and graduate students interested in data privacy, as well as professionals wanting a concise overview.
Vicenç Torra is Professor with the Department of Computing Science at Umeå University, Umeå, Sweden.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Guide to Data Privacy
Book Subtitle: Models, Technologies, Solutions
Authors: Vicenç Torra
Series Title: Undergraduate Topics in Computer Science
DOI: https://doi.org/10.1007/978-3-031-12837-0
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 2022
Softcover ISBN: 978-3-031-12836-3Published: 05 November 2022
eBook ISBN: 978-3-031-12837-0Published: 04 November 2022
Series ISSN: 1863-7310
Series E-ISSN: 2197-1781
Edition Number: 1
Number of Pages: XVI, 313
Number of Illustrations: 27 b/w illustrations, 6 illustrations in colour
Topics: Privacy, Systems and Data Security, Cryptology, Ethics, Computers and Society