Securing IoMT Healthcare Systems with Energy-Efficient Data Transmission and Joint Security Measures

The emergence of wearable medical devices through the Internet of Medical Things (IoMT) has enabled the development of smart healthcare applications, making it easier to monitor patients in real time. While IoMT offers great benefits, ensuring longer network life is the biggest challenge due to energy constrained sensor nodes. Additionally, the communication path used by the IoMT network to transmit sensitive patient data is subject to security risks. Another difficult research problem for healthcare applications is thus ensuring the integrity of registered patient data. This research aims to propose a security-aware and energy-efficient collaborative architecture for the reliable transfer of patient healthcare data via IoMT. The main objectives are to reduce energy consumption in the transmission of health data and to protect patient medical data from malicious attacks to improve the security and efficiency of the IoMT network. First, the patient's vital health data is collected using wearable biosensors attached to the body. Then, the Cognitive Honeybee Colony Optimization Algorithm (CHCOA) is used to select an energy efficient cluster head from a group of nodes in the IoMT. The shortest path between the cluster leader and the base station is identified using a path inference strategy based on fuzzy rules. After identifying an energy-efficient and minimal-distance path, the patient's sensitive biomedical data is encrypted using key policy - attribute-based encryption. The patient's encrypted health data is sent to the recipient in the IoMT network via the selected path.