Application of Differential Privacy Approach in Healthcare Data – A Case Study
Application of Differential Privacy Approach in Healthcare Data – A Case Study
复制标题
差异隐私方法在医疗数据中的应用——案例研究
DOI：
--
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
H. El
中科院分区：
文献类型：
--
作者：
M. Zia;M. A. Khan;H. El
随着物联网的发展及其在各个领域的应用，大量的数据可用并存储在本地和云上的数据库中。医疗保健就是这样一个领域。存储患者医疗数据，通常数据管理员负责确保患者的隐私。在与第三方共享数据以进行进一步分析或研究的情况下，隐私成为主要问题。为了避免此类或类似场景中的任何隐私泄露，本文讨论了差分隐私方法。主要焦点仍然是利用差分隐私的独特属性及其在医疗保健数据中的应用。我们讨论了原始数据中噪声引入量的影响，数据中添加的噪声与数据效用之间的关系，以及数据泄露对侵犯隐私的影响。
With advancement in IoT and its application in various domains, huge amount of data is available and stored in databases both locally and on the cloud. Health care is one such domain. Patient medical data is stored and usually curator of the data is responsible for ensuring privacy of the patient. Privacy becomes the major concern in a scenario, where the data is shared with third party for further analysis or research purposes. To avoid any privacy breach in such or similar scenarios, this article discusses differential privacy approach. Major focus remains exploiting the unique property of differential privacy and its application to healthcare data. We discuss impact of amount of noise introduction in the original data, the relation between the added noise in the data, data utility, and the effect of data leakage to breach of privacy.