What are the main privacy-preserving ML techniques, and how do they differ?

Privacy in ML is a toolbox, not a single switch, and each tool defends a different threat. The signal is mapping DP, federated learning, confidential computing, encryption, and minimization to what they actually protect, and knowing they compose.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.