Healthcare Internet of Things (HIoT) Threat Modelling Using STRIDE-LM

The integration of the Healthcare Internet of Things (HIoT) in health delivery systems has transformed patient care through real-time monitoring and data-driven decision-making, yet it introduces significant cybersecurity vulnerabilities that threaten patient safety and data privacy. The research addresses the critical gap in understanding and modelling cybersecurity threats specific to healthcare environments by applying the STRIDE-LM (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege and Lateral Movement) threat modelling technique to HIoT architectures. Through a Systematic Literature Review (SLR), the research reviewed 35 peer-reviewed publications to examine HIoT’s four-layer architecture (Physical, Network, Processing and Application layers) and categorises cybersecurity threats across the seven STRIDE-LM classifications. The Design Science Research (DSR) methodology was used to model the threats using STRIDE-LM. Distinct threat patterns were identified across the architectural layers, revealing that many medical devices operate with outdated firmware and that critical implementation gaps persist despite widespread threat awareness. The findings demonstrate that STRIDE-LM, when adapted for healthcare contexts to incorporate patient safety considerations, provides literature-based coverage for threat identification and modelling i.e. coverage established against the reviewed literature rather than demonstrated operational effectiveness, enabling healthcare stakeholders to prioritise security investments and develop mitigation strategies that address the unique complexities of healthcare environments.