隐私保护技术应用于医疗保健大数据
Hyunah Shin1, Kyeongmin Ryu1, Jong-Yeup Kim1,2,3
1Department of Healthcare Data Science Center, Konyang University Hospital, Daejeon, Republic of Korea.
Digital health
|November 6, 2024
概括
医疗保健数据安全性至关重要. 本研究审查了区块链,联合学习,同态加密和差异隐私,以加强数据保护并确定大数据隐私的未来研究方向.
科学领域:
- 医疗信息学 医疗信息学
- 数据安全 数据安全
- 计算机科学 计算机科学
背景情况:
- 医疗保健中的大数据的扩散带来了重大的数据安全挑战,导致数据泄露造成的财务损失.
- 越来越需要先进的数据保护技术来保护敏感的健康信息.
- 像联合学习和区块链这样的新兴技术为医疗数据安全提供了潜在的解决方案.
研究的目的:
- 探索和分析医疗保健中广泛使用的隐私技术的研究,方法和局限性.
- 确定医疗保健部门数据保护的最新技术趋势.
- 为当前的隐私技术研究提供见解,并建议未来的研究方向.
主要方法:
- 进行了2017年至2023年期间发表的相关论文的系统审查.
- 专注于四个关键的隐私技术:区块链,联合学习,同态加密和差异隐私.
- 分析了研究,方法,并确定了这些选定的技术的局限性.
主要成果:
- 确定区块链,联合学习,同态加密和差异隐私作为医疗保健中突出的隐私技术.
- 突出了当前的研究格局和医疗数据保护技术趋势.
- 发现了与每个被调查的隐私技术相关的特定限制.
结论:
- 医疗保健中的当前隐私技术存在局限性,需要进一步的研究和开发.
- 该研究提供了对最先进的隐私技术的全面概述,帮助研究人员了解该领域.
- 未来的研究应该专注于解决已识别的局限性,以加强医疗保健数据安全性和隐私.
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