Resources for Technical Privacy

I’ve been spinning up on privacy for a little while now, here are some resources I’ve found helpful:

Summaries

• OpenDP Documentation

• DifferentialPrivacy.org

Textbooks

• The Algorithmic Foundations of Differential Privacy

• Differential Privacy: From Theory to Practice

• Programming Differential Privacy

Blog Series

• Damien Desfontaines

• DifferentialPrivacy.org

• NIST

Course Materials

• Programming Differential Privacy - Joe Near (I really like this one. It’s a quick start for programmers)

• Algorithms for Private Data Analysis - Gautam Kamath

• The Algorithmic Foundations of Data Privacy - Aaron Roth

• Privacy in Statistics and ML - Adam Smith and Jonathan Ullman

• Applied Privacy for Data Science - James Honaker & Salil Vadhan

• Differential Privacy - Marco Gaboardi

• Foundations of Privacy - Moni Naor

Informal Educational Materials

• What is Differential Privacy Basics - Medium

Less Technical Primers

• Differential Privacy: A Primer for a Non-Technical Audience

• Joe Near - Programming Differential Privacy (This is linked above, it’s semi-technical, but it really only requires computer science background, not a mathematical one.)

Code

• OpenDP github

• Opacus (pytorch opensoure DP library for Deep Learning)

Community

• OpenDP

• Harvard Privacy tools