匿名化:在保持隐私的同时使用数据的不完美科学.
Andrea Gadotti1,2, Luc Rocher1,2, Florimond Houssiau1,3
1Imperial College London, Exhibition Road, London SW7 2AZ, UK.
Science advances
|July 17, 2024
概括
安全共享数据需要现代的匿名化技术,而不仅仅是传统的匿名化. 审计这些方法可以确保对科学进步的隐私保护.
科学领域:
- 数据隐私和安全数据隐私和安全
- 信息科学 信息科学
- 计算机科学 计算机科学
背景情况:
- 大量的个人数据来自调查,研究和数字设备.
- 安全的数据共享对于科学和社会进步至关重要.
- 匿名化是最大限度地减少数据共享中的隐私风险的主要方法.
研究的目的:
- 为现代隐私攻击和匿名化技术提供实用性审查.
- 讨论大数据时代传统非识别方法的局限性.
- 探索共享匿名汇总数据的当代方法.
主要方法:
- 审查关于隐私攻击的当前文献.
- 分析传统的非识别技术及其缺点.
- 检查现代匿名化方法,包括数据查询系统,合成数据和差异隐私.
主要成果:
- 传统的非识别方法对于大数据来说是不够的.
- 像差异隐私这样的现代技术提供了改进的数据匿名化.
- 没有单一的匿名化解决方案是完美的.
结论:
- 现代匿名化技术对于安全的数据使用和共享至关重要.
- 对这些技术对隐私攻击的保障进行审计至关重要.
- 结合现代方法和严格的审计,提供了目前最好的数据隐私方法.
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