PET

PETs are tools and techniques that minimize personal data collection and processing while still enabling useful functionality. Examples include differential privacy (adding statistical noise to aggregate queries), k-anonymity (ensuring individuals are indistinguishable in datasets), data masking, and synthetic data generation.

Regulators increasingly expect PETs to be considered when designing data-processing systems.