Security Risk Assessment of IoT for Remote Patient Monitoring System

Abstract

Remote Patient Monitoring (RPM), an essential component of telehealth, is among the biggest changes marked in healthcare. It facilitates patients’ treatment, remotely at home or in some distant location, without traditional clinical settings. The RPM plays a key role in data acquisition, data analysis and insights, and improved healthcare management. It collects real-time data using wearable sensors and mobile apps, and furnish crucial health metrics. Advanced algorithms and prognostic modelling than process the data, pattern and likely health risks to predict any disease more precisely and accurately for early action. RPM provides real-time watch and remote consultation that help in improved disease control and better patients’ care. Improved accuracy, reduced cost, real time interaction, and refined patient well-being are the significant healthcare benefits of RPM. Prognosis Health & Management (PHM) system is used for predicting the remaining useful life (RUL) of healthcare assets such as sensors, pacemakers, defibrillators and other medical equipment. The PHM leads to pre-emptive maintenance, lowers downtime, and tracks the life span of such healthcare equipment. The IoT enables PHM to monitor remote assets and gather instant data to foresee the RUL of such equipment. Providing the facilitations, PHM also creates potential vulnerabilities of exposure of device, network and data, and poses data security and privacy challenges. Therefore, strong security controls are required to keep patients’ data confidential and safe from uneven approaches to technology and data breaches. This paper evaluates risk associated with RPM using OCTAVE ALLGERO, a risk assessment framework, to mitigate the data security concerns.