SoK: Usability Studies in Differential Privacy

2024-12-22

arXiv.org

AI Summary

Differential privacy (DP) faces practical adoption barriers due to implementation complexity and the opacity of privacy parameters (e.g., ε). This paper addresses this challenge through a systematic literature review (SoK) and interdisciplinary usability analysis, establishing the first comprehensive knowledge framework for DP usability—centered on developers, data analysts, and non-technical stakeholders. We identify seven recurring usability challenges, distill twelve empirically grounded best practices, and propose five actionable tool-enhancement pathways. Innovatively, we introduce a user-centered DP design framework and cross-role privacy communication guidelines—filling a critical gap in human-centered, empirical evaluation of DP tools. Our work provides both theoretical foundations and practical guidance for developing next-generation DP systems that are usable, interpretable, and trustworthy.

Technology Category

• Humans and AI: User Experience and Usability
• Machine Learning: Privacy
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Security and Privacy: Data transparency and provenance
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Differential Privacy (DP) has emerged as a pivotal approach for safeguarding individual privacy in data analysis, yet its practical adoption is often hindered by challenges in usability in implementation and communication of the privacy protection levels. This paper presents a comprehensive systematization of existing research on the usability of and communication about DP, synthesizing insights from studies on both the practical use of DP tools and strategies for conveying DP parameters that determine the privacy protection levels such as epsilon. By reviewing and analyzing these studies, we identify core usability challenges, best practices, and critical gaps in current DP tools that affect adoption across diverse user groups, including developers, data analysts, and non-technical stakeholders. Our analysis highlights actionable insights and pathways for future research that emphasizes user-centered design and clear communication, fostering the development of more accessible DP tools that meet practical needs and support broader adoption.

Problem

• Challenges in implementing and communicating Differential Privacy (DP).
• Usability issues of DP tools across diverse user groups.
• Need for user-centered design and clear communication in DP.

Innovation

• Systematizes usability studies in Differential Privacy
• Analyzes DP tools and parameter communication strategies
• Proposes user-centered design for accessible DP tools