Protecting privacy through homomorphic encryption / Kristin Lauter, Wei Dai, Kim Laine (editors)

Contributor(s):

Resource type: Ressourcentyp: BuchBookLanguage: English Publisher: Cham, Switzerland : Springer Nature, 2022Copyright date: © 2021Edition: corrected publicationDescription: xvi, 176, C1 Seiten : IllustrationenISBN:

9783030772864
9783030772888
9783030772895

Subject(s):

Additional physical formats: No title | 9783030772871 | Erscheint auch als: Protecting privacy through homomorphic encryption. Online-Ausgabe. Cham : Springer, 2022. 1 Online-Ressource (xv, 176 Seiten) | Erscheint auch als: Protecting Privacy through Homomorphic Encryption. Online-Ausgabe. 1st ed. 2021. Cham : Springer International Publishing, 2021. 1 Online-Ressource(XVI, 176 p. 35 illus., 28 illus. in color.)DDC classification:

004.0151 23

MSC: MSC: 94-06 | 68-06 | 94A60 | 68P25 | 00B25Summary: This book summarizes recent inventions, provides guidelines and recommendations, and demonstrates many practical applications of homomorphic encryption. This collection of papers represents the combined wisdom of the community of leading experts on homomorphic encryption. In the past 3 years, a global community consisting of researchers in academia, industry, and government, has been working closely to standardize homomorphic encryption. This is the first publication of whitepapers created by these experts that comprehensively describes the scientific inventions, presents a concrete security analysis, and broadly discusses applicable use scenarios and markets. This book also features a collection of privacy-preserving machine learning applications powered by homomorphic encryption designed by groups of top graduate students worldwide at the Private AI Bootcamp hosted by Microsoft Research. The volume aims to connect non-expert readers with this important new cryptographic technology in an accessible and actionable way. Readers who have heard good things about homomorphic encryption but are not familiar with the details will find this book full of inspiration. Readers who have preconceived biases based on out-of-date knowledge will see the recent progress made by industrial and academic pioneers on optimizing and standardizing this technology. A clear picture of how homomorphic encryption works, how to use it to solve real-world problems, and how to efficiently strengthen privacy protection, will naturally become clear.PPN: PPN: 1805843982

Holdings ( 1 )

Holdings
Item type	Home library	Shelving location	Call number	Status	Date due	Barcode	Item holds
Freihandbestand ausleihbar	Fachbibliothek Mathematik	Bibliothek / frei aufgestellt	Inf. / Lau	Available		36538901090

Total holds: 0