Challenges and Opportunities for Conducting Dynamic Risk Assessments in Medical IoT

Abstract

Modern medical devices connected to public and private networks require additional layers of communication and management to effectively and securely treat remote patients. Wearable medical devices, for example, can detect position, movement, and vital signs; such data help improve the quality of care for patients, even when they are not close to a medical doctor or caregiver. In healthcare environments, these devices are called Medical Internet-of-Things (MIoT), which have security as a critical requirement. To protect users, traditional risk assessment (RA) methods can be periodically carried out to identify potential security risks. However, such methods are not suitable to manage sophisticated cyber-attacks happening in near real-time. That is the reason why dynamic RA (DRA) approaches are emerging to tackle the inherent risks to patients employing MIoT as wearable devices. This paper presents a systematic literature review of RA in MIoT that analyses the current trends and existing approaches in this field. From our review, we first observe the significant ways to mitigate the impact of unauthorised intrusions and protect end-users from the leakage of personal data and ensure uninterrupted device usage. Second, we identify the important research directions for DRA that must address the challenges posed by dynamic infrastructures and uncertain attack surfaces in order to better protect users and thwart cyber-attacks before they harm personal (e.g., patients’ home) and institutional (e.g., hospital or health clinic) networks.

Cybersecurity challenges across sustainable development goals: A comprehensive review

“…Medical devices such as wearable health trackers and remote monitoring devices, are vulnerable to cyberattacks which compromise patient safety, privacy, and data integrity [22]. The paper [23] mentions that wearable medical devices connected to the IoT can improve the quality of care for patients, but they also pose threats and vulnerabilities that require attention and mitigative actions. [24] discusses the inadequate security and privacy precautions in IoMT devices, which can lead to patient health data leakage and cyberattacks on medical devices, compromising patient safety and data integrity.…”

Performance of Differential Evolution Algorithms for Indoor Area Positioning in Wireless Sensor Networks

“…It consists of an application layer, network layer, and perception layer, where wireless sensor networks play a crucial role in the network and perception layers, forming part of the IoT infrastructure. Wireless sensor networks construct a network by connecting independent sensor nodes, finding broad applications in home monitoring, military applications, smart cities, environmental monitoring, healthcare fields, and indoor positioning, among other applications [7][8][9][10][11][12][13]. Nevertheless, in such applications, sensor nodes are usually placed in fixed positions and lack mobility.…”