Harvard Data Science Review · 2024 · 35 citations · 240 references
ComputingComputer ScienceSystems EngineeringComputer SecurityPrivacy EngineeringSecurity ArchitectureData PrivacyData ProtectionDifferential PrivacyPrivacy LawPrivacy PolicyPrivacy-preserving ProtocolsDifferential Privacy AuditingPrivacyPrivacy AttacksPrivacy-preserving System DesignPrivacy-utility Trade-offReal-world ApplicationState-of-the-art Review
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 DPâs deployment in real-world applications. Key points and high-level contents of the article were originated from the discussions from âDifferential Privacy (DP): Challenges Towards the Next Frontier,â 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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