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\u2019s deployment in real-world applications. Key points and high-level contents of the article were originated from the discussions from \u201cDifferential Privacy (DP): Challenges Towards the Next Frontier,\u201d 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.<\/p>\n
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.<\/p>\n","protected":false},"excerpt":{"rendered":"
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\u2019s deployment in real-world applications. Key points and high-level contents of the article were originated from the discussions from \u201cDifferential Privacy (DP): Challenges Towards the Next Frontier,\u201d a workshop 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