Privacy-Enhancing Technologies for Artificial Intelligence-Enabled Systems

• URL: http://arxiv.org/abs/2404.03509v1
• Date: Thu, 4 Apr 2024 15:14:40 GMT
• Title: Privacy-Enhancing Technologies for Artificial Intelligence-Enabled Systems
• Authors: Liv d'Aliberti, Evan Gronberg, Joseph Kovba,
• Abstract summary: Artificial intelligence (AI) models introduce privacy vulnerabilities to systems. These vulnerabilities exist during model development, deployment, and inference phases. We propose the use of several privacy-enhancing technologies (PETs) to defend AI-enabled systems.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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