---
title: "Privacy-enhancing technology (PET)"
description: "A technique that reduces what an attacker, vendor or insider can learn from personal data, such as differential privacy, federated learning, synthetic data, masking or trusted execution."
canonical: https://aigovernanceengineer.com/glossary/privacy-enhancing-technology-pet
author: "Jorge García Aibar"
license: "CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)"
doi: https://doi.org/10.5281/zenodo.22956197
version: "0.5.0"
updated: 2026-09-24
---

# Privacy-enhancing technology (PET)

A technique that reduces what an attacker, vendor or insider can learn from personal data, such as differential privacy, federated learning, synthetic data, masking or trusted execution [1]. None makes a system compliant alone; each has a known failure mode and is evidenced by a test.

- Developed in: [ch. 19, Privacy-enhancing technologies and their honest limits](https://aigovernanceengineer.com/bok/privacy-and-ai#privacy-enhancing-technologies-and-their-honest-limits)
- Chapters: [ch. 19, Privacy & AI](https://aigovernanceengineer.com/bok/privacy-and-ai)
- In the glossary chapter: https://aigovernanceengineer.com/bok/glossary#t-privacy-enhancing-technology-pet

## Sources

[1] NIST SP 800-226, Guidelines for Evaluating Differential Privacy Guarantees (differential privacy pyramid; privacy hazards). NIST. 2025-03. https://csrc.nist.gov/pubs/sp/800/226/final (verified: primary)