Securing the Internet of Medical Things: AI-Based Intrusion Detection

Recent advancements in the Internet of Medical Things (IoMT) have had an influence on traditional medical treatment as well as developed data communications in the Smart Healthcare scenario. Unfortunately, this has created a fertile ground for attackers. As a consequence, classic intrusion detection (ID) models as well as innovative detection strategies for IoMT applications have been implemented. Examining the call sequences made by the system processes is one way for determining a typical system behavior. In this paper, an ID system based on Multinomial Naive Bayes was developed. The suggested ID model performed well in terms of accuracy, detection rate, and false alarm rate.