Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866914711172284416 |
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| author | Cummings, Rachel Desfontaines, Damien Evans, David Geambasu, Roxana Huang, Yangsibo Jagielski, Matthew Kairouz, Peter Kamath, Gautam Oh, Sewoong Ohrimenko, Olga Papernot, Nicolas Rogers, Ryan Shen, Milan Song, Shuang Su, Weijie Terzis, Andreas Thakurta, Abhradeep Vassilvitskii, Sergei Wang, Yu-Xiang Xiong, Li Yekhanin, Sergey Yu, Da Zhang, Huanyu Zhang, Wanrong |
| author_facet | Cummings, Rachel Desfontaines, Damien Evans, David Geambasu, Roxana Huang, Yangsibo Jagielski, Matthew Kairouz, Peter Kamath, Gautam Oh, Sewoong Ohrimenko, Olga Papernot, Nicolas Rogers, Ryan Shen, Milan Song, Shuang Su, Weijie Terzis, Andreas Thakurta, Abhradeep Vassilvitskii, Sergei Wang, Yu-Xiang Xiong, Li Yekhanin, Sergey Yu, Da Zhang, Huanyu Zhang, Wanrong |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2304_06929 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment Cummings, Rachel Desfontaines, Damien Evans, David Geambasu, Roxana Huang, Yangsibo Jagielski, Matthew Kairouz, Peter Kamath, Gautam Oh, Sewoong Ohrimenko, Olga Papernot, Nicolas Rogers, Ryan Shen, Milan Song, Shuang Su, Weijie Terzis, Andreas Thakurta, Abhradeep Vassilvitskii, Sergei Wang, Yu-Xiang Xiong, Li Yekhanin, Sergey Yu, Da Zhang, Huanyu Zhang, Wanrong Cryptography and Security 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. |
| title | Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2304.06929 |