Secured healthcare monitoring for remote patient using energy-efficient IoT sensors

Abstract

The Internet of Things (IoT) and cloud computing are found to be effective in providing on-time medical support for patients by storing and accessing their clinical data on servers. There are some issues, such as communication delay, security, and energy loss in IoT sensors, that affect the quality of the service. In this research, a remote patient monitoring system using energy-efficient IoT sensors is proposed to meet security demands. The optimization of network clustering and cluster head selection is performed based on trust, inter- and intra-cluster distance, and energy level by the proposed SS-ROW algorithm, which is formulated by integrating the characteristics of the squirrel and sparrow with Ciphertext Key 2 Policy (CK2P) encryption on data. Further, an effective trust mechanism based on CP-ABE (Ciphertext-Policy Attribute-Based Encryption) and KP-ABE (Key-Policy Attribute-Based Encryption) is established to attain better results in terms of the number of alive nodes, energy left, and throughput.