Privacy-preserving disease detection techniques in e-healthcare systems - Wang, Guoming (Nanyang Technological University, 2020)
With the increasing popularity of pervasive devices such as smartphones, Body Sensor Network(BSN), Internet-of-Things devices and cloud computing, mobile e-healthcare has become a research trend in recent years. Disease detection using big data analytics techniques is a popular e-healthcare research focus. However, big-data disease detection still faces many challenges on privacy of users' sensitive personal information, confidentiality of health service provider's diagnosis model, accuracy of diagnosis, efficiency of query, etc. In this thesis, we aim to improve the security and privacy performance of the e-healthcare systems, while achieving efficient disease detection.