健康数据重新识别:评估对手和潜在危害
Thierry Meurers1, Lena Baum1, Anna Christine Haber1
1Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Center of Health Data Science, Charitéplatz 1, 10117 Berlin, Germany.
了解潜在的对手对于保护生物医学数据共享中的隐私至关重要. 本研究确定了对手类型,动机和危害,以保护健康信息和支持研究.
科学领域:
- 生物医学数据科学是生物医学数据科学.
- 医疗信息学 医疗信息学
- 隐私工程 隐私工程 隐私工程
背景情况:
- 生物医学数据共享加速了疾病的理解和治疗的发展.
- 与强大的隐私保护平衡数据实用性是必不可少的.
- 识别潜在的对手及其动机是缓解重新识别风险的关键.
研究的目的:
- 在生物医学数据共享方面全面列出潜在的对手.
- 根据敌人的动机对敌人进行分类.
- 识别数据重新识别对个人造成的潜在危害.
主要方法:
- 一个由13名研究人员参与的三步研讨会过程.
- 识别潜在的对手.
- 根据动机对敌人进行分类,并扣除相关的伤害.
主要成果:
- 一个28个对手建议的集合.
- 分类成六种不同的对手类型.
- 每种类型与六种不同的潜在危害中的几个类型的关联.
结论:
- 这些发现为评估重新识别风险提供了一个结构化的框架.
- 该研究为制定有效的健康数据共享保护措施提供了基础.
- 了解威胁行为者和结果对于安全的生物医学数据交换至关重要.
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