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Guide Data Privacy Models by Torra Vicenç (14 results)
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Guide to Data Privacy: Models, Technologies, Solutions (Undergraduate Topics in Computer Science)
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Guide to Data Privacy : Models, Technologies, Solutions
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Guide to Data Privacy : Models, Technologies, Solutions
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Guide to Data Privacy: Models, Technologies, Solutions
Published by Springer-Nature New York Inc, 2022
ISBN 10: 3031128362 ISBN 13: 9783031128363
Language: English
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Add to basketPaperback. Condition: Brand New. 329 pages. 9.25x6.10x0.69 inches. In Stock.
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Guide to Data Privacy : Models, Technologies, Solutions
Published by Springer International Publishing, 2022
ISBN 10: 3031128362 ISBN 13: 9783031128363
Language: English
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data privacy technologies are essential for implementing information systems with privacy by design.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 usersOffers characterization of privacy models, comparing their differences, advantages, and disadvantagesDescribes some of the most relevant algorithms to implement privacy modelsIncludes examples of data protection mechanismsThis 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 Torrais Professor with the Department of Computing Science at Umeå University, Umeå, Sweden.
