Risk-adaptive access control model for big data in healthcare

被引：19

作者：

Hui, Zhen ^{[1
]}

Li, Hao ^{[1
]}

Zhang, Min ^{[1
]}

Feng, Deng-Guo ^{[1
]}

机构：

[1] Institute of Software, Chinese Academy of Sciences, Beijing,100080, China

来源：

Tongxin Xuebao/Journal on Communications | 2015年 / 36卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Access control models - Health care - Data privacy;

D O I：

10.11959/j.issn.1000-436x.2015328

中图分类号：

学科分类号：

摘要：

While dealing with the big data in healthcare, it was difficult for a policy maker to foresee what information a doctor may need, even to make an accurate access control policy. To deal with it, a risk-based access control model that regulates doctors' access rights adaptively was proposed to protect patient privacy. This model analyzed the history of access, applies the EM algorithm and the information entropy technique to quantify the risk of privacy violation. Using the quantified risk, the model can detect and control the over-accessing and exceptional accessing of patients' data. Experimental results show that this model is effective and more accurate than other models. © 2015, Editorial Board of Journal on Communications. All right reserved.

引用