电子医疗多属性大数据安全加密与仿真  

Electronic Medical Multi-Attribute Big Data Security Encryption and Simulation

作　　者：翟曦 田明[1] 段少军 ZHAI Xi;TIAN Ming;DUAN Shao-jun(Hebei Children's Hospital,Hebei University,Shijiazhuang Hebei 050000,China)

机构地区：[1]河北大学河北省儿童医院,河北石家庄050000

出　　处：《计算机仿真》2025年第1期372-376,共5页Computer Simulation

基　　金：河北省科技计划项目(21550303D)。

摘　　要：电子医疗数据中包含大量的敏感信息,在对其加密时,若不能及时对敏感数据实施匿名化隐藏,并确保仅具备特定属性的用户方能访问,则会显著增加数据泄露的风险。因此,提出海量电子医疗大数据多属性基加密方法。通过层次分析对医疗数据准标识属性确定,完成敏感数据效用排序,利用K-匿名算法对海量医疗大数据实施匿名化处理。采用各个认证机构独立生成电子医疗大数据系统主私钥份额以及各自公私钥,实现医疗数据的属性基加密。实验结果表明,利用上述方法开展数据加密时,加密效果好、性能高。Electronic medical data contains a lot of sensitive information.When encrypting it,if the sensitive data can't be anonymously hidden in time and only users with specific attributes can access it,the risk of data leakage will be significantly increased.Therefore,a multi-attribute base encryption method for massive electronic medical big data is proposed.Through the Analytic Hierarchy Process(AHP),the quasi-identification attributes of medical data are determined,and the utility ranking of sensitive data is completed.The K-anonymity algorithm is used to anonymize massive medical big data.The attribute-based encryption of medical data is realized by using each certification body to independently generate the master and private key share of the electronic medical big data system and their own public and private keys.The experimental results show that the encryption effect is good and the performance is high when using the above method to encrypt data.

关 键 词：电子医疗大数据 多属性 基加密方法 敏感数据匿名化 认证机构独立 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]