Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment
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.
Keywords
Cite
@article{arxiv.2304.06929,
title = {Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment},
author = {Rachel Cummings and Damien Desfontaines and David Evans and Roxana Geambasu and Yangsibo Huang and Matthew Jagielski and Peter Kairouz and Gautam Kamath and Sewoong Oh and Olga Ohrimenko and Nicolas Papernot and Ryan Rogers and Milan Shen and Shuang Song and Weijie Su and Andreas Terzis and Abhradeep Thakurta and Sergei Vassilvitskii and Yu-Xiang Wang and Li Xiong and Sergey Yekhanin and Da Yu and Huanyu Zhang and Wanrong Zhang},
journal= {arXiv preprint arXiv:2304.06929},
year = {2024}
}