Smart health: A sophisticated framework designed integrated with Internet of Things (IoT) service applications through the utilization of machine learning techniques
Sambit Satpathy, Dhirendra Kumar Shukla, Arvind Dagur · 2025
Previous security problems have arisen as a result of the intricate operations of Smart Healthcare Systems (SH). The attackers are enabled to disrupt the functioning of the SH system by several means, including as injecting fake data to substitute important indicators and interfering with medical equipment to prevent the notification of crucial circumstances. This study introduces a new machine learning-based framework called Smart Health, which aims to enhance the security of Internet of Medical Things (IoMT) devices in Smart Home Systems (SHS). Smart Health watches monitor the vital signs collected by various Internet of Medical Things (IoMT) devices to assess changes in different bodily functions, distinguishing between routine activities and potentially harmful security breaches. The performance of the Smart Health system is evaluated for three distinct hazardous assaults. During the examination of performance, it has been noted that Smart Health can accurately detect malicious activity in IoMT 92% of the time, achieving an F1-score of 90%.