Work

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

Year: 2025

Type: article

Abstract: 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.

Source: ICT Express

DOI: 10.1016/j.icte.2025.11.005

Authors: Syed Rizwan Hassan, Muhammad Usama Tanveer, Sunil Prajapat, Mohammad Shabaz

Institutions: Gachon University, Khwaja Fareed University of Engineering and Information Technology, Central University of Himachal Pradesh, Marwadi University

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,500