Placeholder text

Go to cart

Practical Data Privacy

By Katharine Jarmul

Practical Data Privacy Computer Science

Practical Data Privacy

0 - Used - very good
Description
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?
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
344
Release Date:
2023-06-06
Publication Date:
2023-06-06
Publisher:
O'Reilly Media
Languages:
Original: English
ISBN10:
1098129466
ISBN13:
9781098129460
GPSR Manufacturer Reference:
[email protected]
Weight:
616 g
Height:
176 cm
Width:
232 cm
Thickness:
19 cm
Currently sold out