用信息理论隐私隐藏敏感基因型的机制
Fangwei Ye1, Hyunghoon Cho2, Salim El Rouayheb3
1Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
IEEE transactions on information theory
|June 7, 2023
概括
分享个人基因组数据需要隐私. 这项研究引入了一种新的机制来保护敏感的遗传信息,确保隐私,同时实现数据共享. 该方法提供了强大的保护,防止基因型泄漏.
科学领域:
- 基因组学就是基因组学.
- 信息理论 信息理论
- 计算机科学 计算机科学
背景情况:
- 个人基因组学服务正在增加,引发了对基因组数据隐私的担忧.
- 分享基因组序列可以无意中揭示敏感的健康相关信息.
- 由于遗传位置之间的相关性,简单地掩盖基因型是不够的.
研究的目的:
- 开发一个信息理论上的隐私机制来共享基因组数据.
- 为了确保敏感的基因型在释放其他序列信息时保持隐藏.
- 为了实现完美的信息理论隐私,基因组数据共享.
主要方法:
- 引入了一个基于删除的隐私机制.
- 解释该机制为一个贪的算法优化位置释放.
- 分析了通过隐藏的马尔科夫模型建模的序列的计算复杂性.
- 由于错误的先前分发而导致的有限隐私泄露.
主要成果:
- 拟议的机制实现了完美的信息理论隐私,使释放的序列在统计学上独立于敏感的基因型.
- 找到该机制的最佳处理顺序是NP-hard.
- 为隐藏的马尔科夫模型序列开发了一种高效的多项式时间算法.
- 该机制证明了对先前分布估计中的错误的稳定性.
结论:
- 开发的基于删除的机制为基因组数据共享中的隐私提供了严格的解决方案.
- 这些发现为加强对个人基因组学敏感信息的控制提供了一条途径.
- 进一步的研究可以在这个基础上建立更安全的基因组数据应用.
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