Privacy-Aware Efficient Fine-Grained Data Access Control in Internet of Medical Things Based Fog Computing - Xiaofan Wang; Lei Wang; Yujun Li; Keke Gai (IEEE Access, 2018)
The recent development of cloud computing has empowered the Internet-based services, which enable users to gain a broad scope of access to their applications, such as Internet of Medical Things (IoMT). Considering the efficiency performance, the privacy protection is often kept at a lower level in order to ensure the application can offer a higher level performance. However, this mechanism also causes a serious concern of privacy hazards due to the information over collections operated by apps/applications. Addressing this privacy issue, this paper proposes an approach that is designed to provide high-level privacy protection without lowering down the efficiency in cloud/fog computing (especially in biological systems of IoMT). The proposed model is called fog-based access control model. The fine-grained data access control is combined with the implementation of fog computing in the proposed approach. Our simulation experiment has shown that our approach could offer high-level privacy protection within a shortened execution time, thus it can be useful for IoMT-based applications.