Protecting Privacy through Homomorphic Encryption

Kim Laine, Kristin Lauter, Wei Dai, 2023
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Product details

The book "Protecting Privacy through Homomorphic Encryption" offers a comprehensive overview of recent developments in the field of homomorphic encryption. It brings together insights from leading experts and serves as a valuable resource for professionals and enthusiasts who wish to engage with this innovative cryptographic technology. Over the past three years, a global community of researchers from academia, industry, and government has been working intensively on standardizing homomorphic encryption. This publication includes the first white papers that detail the scientific inventions, present a concrete security analysis, and discuss various use cases and markets. Additionally, it showcases practical applications in the area of privacy-friendly machine learning, developed by talented students as part of Microsoft's Private AI Bootcamp. The book aims to provide access to this important technology for non-experts and to inspire them.

Key specifications

topic
Mathematics & Natural Sciences
Author
Kim LaineKristin LauterWei Dai
Year
2023
Book cover
Paperback

General information

Item number
56918770
Publisher
Springer
Category
Reference books
Release date
27.3.2025

Book properties

topic
Mathematics & Natural Sciences
Author
Kim LaineKristin LauterWei Dai
Year
2023
Book cover
Paperback

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