Practical data privacy : enhancing privacy and security in data / Katharine Jarmul.

Includes index.

Data governance and simple privacy approaches -- Anonymization -- Building privacy into data pipelines -- Privacy attacks -- Privacy-aware machine learning and data science -- Federated learning and data science -- Encrypted computation -- Navigating the legal side of privacy -- Privacy and practicality considerations -- Frequently asked questions (and their answers!) -- Go forth and engineer privacy!

Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems.