A comprehensive survey on intrusion detection in internet of medical things: Datasets, federated learning, blockchain, and future research directions

The emerging Internet of Medical Things (IoMT) architecture enables real-time processing and monitoring of medical information. Its growing applications expose it to sophisticated cyber threats. Intrusion Detection Systems (IDS) have therefore become indispensable in ensuring confidentiality, integrity, and regulatory compliance. Existing surveys address the security issues, but they lack dataset analysis and integration of emerging approaches. This review presents a systematic review that classifies IoMT-IDSs across deployment strategies, response mechanisms, and evaluation metrics. We develop a multi-dimensional taxonomy that highlights the gaps and outlines a roadmap with federated IDS, blockchain validation, and explainable AI for secure healthcare.