摘要
分析生物医学数据流通难点、传统隐私保护手段缺陷,介绍隐私计算优势及其主流技术路线,阐述生物医学中隐私计算的典型应用场景和有关案例,为该领域相关研究提供参考。
The paper analyzes the difficulties of biomedical data sharing and the defects of traditional privacy protection methods,introduces the advantages of privacy-preserving computing and its mainstream technology route,and expounds the typical application scenarios and related cases of privacy-preserving computing in the biomedical field,so as to provide references for related research in this field.
作者
辛均益
陈如梵
王林
唐丹叶
孙琪
沈涛
王爽
XIN Junyi;CHEN Rufan;WANG Lin;TANG Danye;SUN Qi;SHEN Tao;WANG Shuang(Hangzhou Medical College,Hangzhou 310059,China;Hangzhou Nuowei Information Technology Co.Ltd.,Hangzhou 310053,China;Jinan University,Jinan 250022,China;CAIQTEST Group,Beijing 100176,China;West China Hospital,Sichuan University,Chengdu 610041,China)
出处
《医学信息学杂志》
CAS
2022年第10期2-7,共6页
Journal of Medical Informatics
关键词
隐私计算
生物医学数据
数据流通
联邦学习
可信执行环境
privacy-preserving computing
biomedical data
data sharing
federated learning
trusted execution environment