Intrusion Detection System for Defending against DoS Attacks in the IoMT Ecosystem

This paper endeavors to enhance healthcare security in the Internet of Medical Things (IoMT) by developing an Intrusion Detection System (IDS) focused on countering Denial of Service (DoS) attacks. Leveraging machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF), Linear Discriminant Analysis (LDA), and k-Nearest Neighbors (k-NN), the IDS is trained on Wireshark-simulated data to identify and mitigate DoS threats. By filling critical gaps in IoMT cybersecurity literature and providing a dataset for IoMT-based DoS attacks, this work fortifies the resilience of IoMT infrastructure, safeguarding health data, healthcare service continuity, and patient safety in our increasingly interconnected healthcare landscape.