Practical Data Privacy

Practical Data Privacy Enhancing Privacy and Security in Data

Paperback (12 May 2023)

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Publisher's Synopsis

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.

Practical Data Privacy answers important questions such as:

  • What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases?
  • What does "anonymized data" really mean? How do I actually anonymize data?
  • How does federated learning and analysis work?
  • Homomorphic encryption sounds great, but is it ready for use?
  • How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help?
  • How do I ensure that my data science projects are secure by default and private by design?
  • How do I work with governance and infosec teams to implement internal policies appropriately?

Book information

ISBN: 9781098129460
Publisher: O'Reilly Media
Imprint: O'Reilly
Pub date:
Language: English
Number of pages: 344
Weight: 616g
Height: 177mm
Width: 234mm
Spine width: 21mm