Patients’ Mental Health Data and Internet of Medical Things (IoMT) Safety: Analyzing Raspberry pi vulnerabilities

Abstract

Objective: The goal of this study us to evaluate the safety of patient’s data in an Internet of Medical Things (IoMT) ecosystem. The study focuses on three main objectives: To assess the vulnerability of IoMT devices and systems to cyber threats and data breaches. Specifically, we look at the vulnerability of the raspberry pi servers that are considered the essential building block of an IOT/IOMT environment; to pinpoint vulnerability areas of IoMT ecosystem; and to identify and propose mitigation strategies for the key risks associated with the IoMT ecosystem. Methodology The study employed setting up a representative IOMT model where a raspberry pi server controls the IOMT devices. Specifically, we address the following: 1. Vulnerability Assessment: An empirical analysis of a range of IoMT devices and systems was performed to identify specific vulnerabilities. This involved penetration testing and security assessments in controlled environments. 2. Identify the mitigation strategies to gauge the effectiveness. 3. Test the effectiveness of the mitigation strategies. Results: The study highlights several critical vulnerabilities within the IoMT ecosystem such as weak encryption methods, lack of proper monitoring, effective authentication mechanisms, and the use of outdated software. The study showed that the underlying raspberry pi server are vulnerable to common cyberattack vectors. However, such vulnerabilities can be countered by effective mitigation techniques allowing to capitalize on the IoMT ecosystem. Conclusion: The study confirms the need for ongoing monitoring and improvement in the IoMT ecosystem. Given the continuous advances in the technology field, the healthcare practitioners and administrators need to put a string governance process in place to ensure the continuous monitoring of potential vulnerabilities and in turn providing an effective remedy.