Livraga | Protecting Privacy in Data Release | Buch | 978-3-319-35525-2 | sack.de

Buch, Englisch, Band 57, 192 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 3226 g

Reihe: Advances in Information Security

Livraga

Protecting Privacy in Data Release


Softcover Nachdruck of the original 1. Auflage 2015
ISBN: 978-3-319-35525-2
Verlag: Springer International Publishing

Buch, Englisch, Band 57, 192 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 3226 g

Reihe: Advances in Information Security

ISBN: 978-3-319-35525-2
Verlag: Springer International Publishing


This book presents a comprehensive approach to protecting sensitive information when large data collections are released by their owners. It addresses three key requirements of data privacy: the protection of data explicitly released, the protection of information not explicitly released but potentially vulnerable due to a release of other data, and the enforcement of owner-defined access restrictions to the released data. It is also the first book with a complete examination of how to enforce dynamic read and write access authorizations on released data, applicable to the emerging data outsourcing and cloud computing situations. Private companies, public organizations and final users are releasing, sharing, and disseminating their data to take reciprocal advantage of the great benefits of making their data available to others. This book weighs these benefits against the potential privacy risks. A detailed analysis of recent techniques for privacy protection in data release and case studies illustrate crucial scenarios. Protecting Privacy in Data Release targets researchers, professionals and government employees working in security and privacy. Advanced-level students in computer science and electrical engineering will also find this book useful as a secondary text or reference.

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Zielgruppe


Research


Autoren/Hrsg.


Weitere Infos & Material


Introduction.- Related Work.- Enforcing Confidentiality and Visibility Constraints.- Counteracting Inferences from Sensitive Volume Distributions.- Enforcing Dynamic Read and Write Priviledges.- Conclusions.



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