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

14 April 2023
Rachel Cummings
Damien Desfontaines
David Evans
Roxana Geambasu
Yangsibo Huang
Matthew Jagielski
Peter Kairouz
Gautam Kamath
Sewoong Oh
O. Ohrimenko
Nicolas Papernot
Ryan M. Rogers
Milan Shen
Shuang Song
Weijie Su
Andreas Terzis
Abhradeep Thakurta
Sergei Vassilvitskii
Yu Wang
Li Xiong
Sergey Yekhanin
Da Yu
Huanyu Zhang
Wanrong Zhang
ArXiv (abs)PDFHTML
Abstract

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

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