Privacy-preserving measurement and machine learning

What this post added

This post details Cloudflare's participation in the IETF's Privacy Preserving Measurement working group and their implementation of the Distributed Aggregation Protocol (DAP) in their open-source aggregator server, Daphne. It explains the core principles of DAP, including data minimization and the use of secret sharing and multi-party computation to aggregate data without exposing individual measurements. The post also discusses challenges like input validation and non-linear aggregation, and how zero-knowledge proofs and Prio are used to address them.