信息网络安全 ›› 2018, Vol. 18 ›› Issue (9): 48-54.doi: 10.3969/j.issn.1671-1122.2018.09.008

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一种大数据环境下医疗隐私保护方案设计与实现

胡荣磊, 何艳琼, 曾萍, 范晓红   

  1. 北京电子科技学院,北京 100070
  • 收稿日期:2018-07-17 出版日期:2018-09-30 发布日期:2020-05-11
  • 作者简介:

    作者简介:胡荣磊(1977—),男,河北,副研究员,博士,主要研究方向为通信与网络安全;何艳琼(1993—),女,湖北,硕士研究生,主要研究方向为信息安全、大数据安全;曾萍(1969—),女,河南,教授,博士,主要研究方向为物联网安全;范晓红(1979—),女,山西,讲师,硕士,主要研究方向为计算机网络、云安全。

  • 基金资助:
    国家自然科学基金面上项目[61772047];中央高校基本科研业务费[BESTI-2017LG-01]

Design and Implementation of Medical Privacy Protection Scheme in Big Data Environment

Ronglei HU, Yanqiong HE, Ping ZENG, Xiaohong FAN   

  1. Beijing Electronic Science & Technology Institute, Beijing 100070, China
  • Received:2018-07-17 Online:2018-09-30 Published:2020-05-11

摘要:

随着医疗信息系统的应用,数据共享和数据分析使得医疗隐私更加透明,单一的数据加密技术很难解决隐私泄露问题,因此需要一个完整的医疗隐私保护方案。文章提出了一种大数据环境下的隐私保护方案,方案结合大数据平台技术和存储技术对医疗数据进行脱敏处理,制定隐私保护策略,根据不同的脱敏方案调用不同的脱敏方法,有效保护了隐私信息。文章对系统的核心功能模块进行编程实现,保证了数据的分布特征不变,并使得处理后的数据集不再明显含有个体隐私信息。文章最后对系统性能进行了测试,验证了系统的可行性和可靠性。

关键词: 大数据, 隐私保护, 数据脱敏, 隐私泄露

Abstract:

With the application of medical information systems, data sharing and data analysis make medical privacy more transparent, and a single data encryption technology is difficult to solve the problem of privacy leakage, so it needs a complete medical privacy protection program. This paper proposes a privacy protection scheme under the big data environment. This scheme combines the big data platform technology and storage technology to desensitize the medical data, formulate privacy protection strategies, and call different desensitization methods according to different desensitization schemes, which can effectively protect privacy information. The core functional modules of the system are programmed and implemented. In the system implementation, the distribution characteristics of the data can be ensured, and the processed data set no longer contains individual private information. System performance was tested to verify the feasibility and reliability of the system.

Key words: big data, privacy protection, data desensitization, privacy leakage

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