The security and privacy of your user’s data is vital for them to trust your applications. But identity theft, data leaks, and deliberate attacks threaten those vital secrets, and leave personal information exposed and vulnerable. Whether you’re working as a developer or even a machine learning engineer, ensuring that your software is secure is a mandatory practice.
about the book
Exploring Security, Privacy, and Trust
spotlights three chapters from Manning books chosen by tech privacy guru Nishant Bhajaria. In them, you’ll connect the dots between privacy outcomes and data-related decisions, examine fairness and how to identify sources of bias, and take a look at the problems that Self-Sovereign Identity aims to help solve as well as the quickly evolving factors in this major paradigm shift. By the time you’re done, you’ll understand the time for preserving your users’ privacy and earning their trust is now. Get started with this value-packed free mini ebook!
- “Data privacy: understanding ‘data’ and ‘privacy’ ” – Chapter 2 from Data Privacy by Nishant Bhajaria
- “Fairness and mitigating bias” – Chapter 8 from Interpretable AI by Ajay Thampi
- “Why the internet is missing an identity layer—and why SSI can finally provide one” – Chapter 1 from Self-Sovereign Identity by Alex Preukschat and Drummond Reed
about the author
leads the Technical Privacy and Strategy teams for Uber. He heads a large team that includes data scientists, engineers, privacy experts and others as they seek to improve data privacy for the customers and the company. His role has significant levels of cross-functional visibility and impact. Previously he worked in compliance, data protection, security, and privacy at Google. He was also the head of privacy engineering at Netflix. He is a well-known expert in the field of data privacy, has developed numerous courses on the topic, and has spoken extensively at conferences and podcasts.