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Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment

Published onJan 16, 2024
Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment
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You're viewing an older Release (#1) of this Pub.

  • This Release (#1) was created on Jan 16, 2024 ()
  • The latest Release (#3) was created on Feb 01, 2024 ().

Abstract

In this paper, we present a detailed review of current practices and state-of-art methodologies in the field of Differential Privacy (DP), with a focus of advancing DP’s deployment in real-world applications. Key points and high-level contents of the paper was originated from the discussions from “Differential privacy (DP): Challenges towards the next frontier,” a workshop held in July 2022 with experts from industry, academia, and the public sector seeking answers to broad questions pertaining to privacy and its implications in the design of industry-grade systems.

This paper aims to provide a reference point for the algorithmic and design decisions within the realm of privacy, highlighting the important challenges and potential research directions. Covering a wide spectrum of topics, this paper delves into the infrastructure needs for designing private systems, methods for achieving better privacy/utility trade-offs, privacy attacks and auditing, as well as communicating privacy with broader audiences and stakeholders.

Keywords: differential privacy, privacy infrastructure, utility trade-offs, privacy protection



01/16/2024: To preview this content, click below for the Just Accepted version of the article. This peer-reviewed version has been accepted for its content and is currently being copyedited to conform with HDSR’s style and formatting requirements.


©2024 by Rachel Cummings, David Evans, Damien Desfontaines, Roxana Geambasu, Yangsibo Huang, Matthew Jagielski, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, and Wanrong Zhang. This article is licensed under a Creative Commons Attribution (CC BY 4.0) International license, except where otherwise indicated with respect to particular material included in the article.

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