Recent Advances in the Internet-of-Medical-Things (IoMT) Systems Security

Abstract

The rapid evolutions in micro-computing, minihardware manufacturing, and machine to machine (M2M) communications have enabled novel Internet of Things (IoT) solutions to reshape many networking applications. Healthcare systems are among these applications that have been revolutionized with IoT, introducing an IoT branch known as the Internet of Medical Things (IoMT) systems. IoMT systems allow remote monitoring of patients with chronic diseases. Thus, it can provide timely patients' diagnostic that can save their life in case of emergencies. However, security in these critical systems is a major challenge facing their wide utilization.In this paper, we present state-of-the-art techniques to secure IoMT systems' data during collection, transmission, and storage. We comprehensively overview IoMT systems' potential attacks, including physical and network attacks. Our findings reveal that most security techniques do not consider various types of attacks. Hence, we propose a security framework that combines several security techniques. The framework covers IoMT security requirements and can mitigate most of its known attacks.

An IoT Framework for Screening of COVID-19 Using Real-Time Data from Wearable Sensors

“…All the communication taking place between different components is secured: HTTP with SSL encryption and MQTT with TLS encryption. In addition, Ubidots use token-based secure authorization [68,69]. As the sensors do not provide any data storage and the sensors' readings are directly sent to the cloud, user's data is not exposed.…”

Internet of Things, Preliminaries and Foundations

“…Recently, a growing desire has been witnessed to make the healthcare environments (e.g., hospitals, medical institutions, health centers) more tailored, cost-efficient, and dynamic which coincides with advancement in IoT technology making it the most promising solution for satisfying the emerging requirements of healthcare systems and thereby improving the quality of medical services. The introduction of IoT system into medical or healthcare environments bring us with a new subset of generic IoT platform called the Internet of Medical Things (IoMT) [39], or sometimes referred to as the Internet of Healthcare Things (IoHT) [40]. Different from the generic IoT system that mainly depends on Wireless Sensor Networks (WSNs), the IoMT mainly relies on the Body Sensor Networks (BSNs) which is a network established using a set of connected sensing devices deployable at different parts of the human body.…”

“…Securing cloud servers can entail authentication and approval procedures to restrict access to the IoT service and applications. One more essential security technique is the control of the identity of the device to confirm its reliability before permitting it to access the cloud [39].…”

Decentralized Federated Learning for Healthcare Networks: A Case Study on Tumor Segmentation

“…Combined with the human pathologist's inputs, AI systems have contributed to significantly reduce the human error rate [1]. On the other hand, the increasing volume of data, the widespread adoption of Internetof-Medical-Things (IoMT) [2] and AI-enabled devices with high computing capabilities, have made conventional central-ized (Big-Data) learning solutions inefficient in terms of latency and scalability due to the need of moving, often periodically, large datasets. Besides, regulatory authorities as well as patient organizations are proposing stringent limitations to AI-driven data processing, to ensure that private data is not shared or transferred to third parties, even in anonymized format [3].…”