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- Toujours un magasin près de chez vous
Homomorphic Encryption for Data Science (He4ds)
Allon Adir, Ehud Aharoni, Nir Drucker, Ronen Levy, Hayim Shaul, Omri Soceanu
Livre relié | Anglais
80,45 €
+ 160 points
Description
This book provides basic knowledge required by an application developer to understand and use the Fully Homomorphic Encryption (FHE) technology for privacy preserving Data-Science applications. The authors present various techniques to leverage the unique features of FHE and to overcome its characteristic limitations.
Specifically, this book summarizes polynomial approximation techniques used by FHE applications and various data packing schemes based on a data structure called tile tensors, and demonstrates how to use the studied techniques in several specific privacy preserving applications. Examples and exercises are also included throughout this book.
The proliferation of practical FHE technology has triggered a wide interest in the field and a common wish to experience and understand it. This book aims to simplify the FHE world for those who are interested in privacy preserving data science tasks, and for an audience that does not necessarily have a deep cryptographic background, including undergraduate and graduate-level students in computer science, and data scientists who plan to work on private data and models.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 304
- Langue:
- Anglais
Caractéristiques
- EAN:
- 9783031654930
- Date de parution :
- 10-11-24
- Format:
- Livre relié
- Format numérique:
- Genaaid
- Dimensions :
- 156 mm x 234 mm
- Poids :
- 635 g
