相关实验视频
Updated: Jul 13, 2025

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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
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对披露风险评估要求进行深入审查
Ron S Jarmin1, John M Abowd2, Robert Ashmead1
1U.S. Census Bureau, Office of the Deputy Director, Washington, DC 20233.
概括
评估人口普查数据隐私方法至关重要. 反事实比较为隐私与实用分析提供了最佳的平衡,尽管在满足所有隐私标准方面存在挑战.
科学领域:
- 统计 统计 统计 统计
- 计算机科学 计算机科学
- 社会科学 社会科学 社会科学
背景情况:
- 正式的隐私方法保护机密的人口普查数据.
- 讨论了数据产品的披露风险和社会效益的衡量.
- 2020年十年人口普查强调了对强大的隐私指标的需求.
研究的目的:
- 为量化披露风险提出客观标准.
- 为了评估人口普查数据的不同隐私框架.
- 确定最适合的隐私效用分析方法.
主要方法:
- 绝对披露风险框架的评估.
- 对反事实框架 (差异隐私) 的分析.
- 前后两种方法的比较.
主要成果:
- 没有一个框架能够完美满足所有隐私需求.
- 反事实比较最好平衡隐私和实用性.
- 绝对披露风险框架满足了最少的标准.
结论:
- 客观的标准对于量化披露风险至关重要.
- 反事实方法对人口普查数据的隐私来说是最有希望的.
- 需要进一步的研究,但推使用反事实方法进行短期分析.
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