解析联邦政府应用差分隐私的挑战与机遇，助力数据安全与效率提升
Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government
- 从技术、法律、实践三方面揭示差分隐私在政府应用中的障碍
- 提出双版本分析发布与密级任务人员配置优化两大可行场景
- 面向政策制定者、隐私监管者及数据安全人员的实用指南
本文由差分隐私研究人员、隐私律师和数据科学家组成的团队撰写，旨在阐明差分隐私在美国联邦政府环境下的挑战与机遇。在介绍差分隐私基本概念后，重点指出当前制约其应用的三大挑战。随后通过两个实例展示其潜力：一是允许政策安全官员以不同隐私水平发布多版本分析结果；二是首次提出差分隐私可用于提升密级任务中的人员配置效率。本文力求为差分隐私研究社区、隐私监管机构、安全官员和立法者提供非技术性参考，推动未来行动决策。
原文摘要 · Abstract (English)
In this article, we seek to elucidate challenges and opportunities for differential privacy within the federal government setting, as seen by a team of differential privacy researchers, privacy lawyers, and data scientists working closely with the U.S. government. After introducing differential privacy, we highlight three significant challenges which currently restrict the use of differential privacy in the U.S. government. We then provide two examples where differential privacy can enhance the capabilities of government agencies. The first example highlights how the quantitative nature of differential privacy allows policy security officers to release multiple versions of analyses with different levels of privacy. The second example, which we believe is a novel realization, indicates that differential privacy can be used to improve staffing efficiency in classified applications. We hope that this article can serve as a nontechnical resource which can help frame future action from the differential privacy community, privacy regulators, security officers, and lawmakers.
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