# Privacy-Enhancing Technologies for Artificial Intelligence-Enabled Systems

arXiv: https://arxiv.org/abs/2404.03509 · HTML: https://mlsanity.com/paper/2404.03509/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Apr 2024.

## Built on by (most cited first, 1 of 1)

- [Securing Generative AI in Healthcare: A Zero-Trust Architecture Powered by Confidential Computing on Google Cloud](https://mlsanity.com/paper/2511.11836/) (2025)

## Abstract (arXiv)

Artificial intelligence (AI) models introduce privacy vulnerabilities to systems. These vulnerabilities may impact model owners or system users; they exist during model development, deployment, and inference phases, and threats can be internal or external to the system. In this paper, we investigate potential threats and propose the use of several privacy-enhancing technologies (PETs) to defend AI-enabled systems. We then provide a framework for PETs evaluation for a AI-enabled systems and discuss the impact PETs may have on system-level variables.