Privacy Enhancing Technologies Presentation & References
Presentation
•Intro to Homomorphic Encryption ;
How would you explain homomorphic encryption?
•autodp: Automating differential privacy computation•
Differentially Private Analytics at Scale•
PRIVIC: A privacy-preserving method for incremental collection of location data•
FLOWER: A Friendly Federated Learning Framework•
Google Differential Privacy Library•
Analyzing Leakage of Personally Identifiable Information in Language Models•
EzPC: Easy Secure Multiparty Computation•
A Pragmatic Introduction to Secure Multi-Party Computation•Zero Knowledge Proofs: An illustrated primer•Google Differential Privacy Library•
PySyft DP Library•Designing Access with Differential Privacy – MIT Handbook of Using Admin Data for Research•
Apple’s Differential Privacy ;
Apple’s Learning with Privacy at Scale
•Google’s Big Query Differential Privacy ;