Protecting Privacy through Homomorphic Encryption

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 Readers who have preconceived biases  based on out-of-date knowledge will see the recent progress made by  industrial and academic pioneers on optimizing and standardizing this  technology.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.