Authors: Durjoy Datta
Abstract: The integration of Internet of Things (IoT) technologies into healthcare systems has revolutionized the way medical services are delivered, enabling more accurate diagnostics, real-time monitoring, and personalized treatment. This rapid digital transformation, however, comes with a set of significant security risks. As healthcare devices become increasingly connected, the potential for cyber threats grows, exposing systems to breaches that can compromise patient data, disrupt clinical operations, or even endanger lives. Despite the numerous advantages, many IoT devices are deployed with inadequate security features, making them susceptible to hacking, data leakage, and unauthorized control. In the context of smart healthcare, where devices interact continuously with sensitive patient data and other critical systems, the need for robust risk modeling becomes imperative. This article comprehensively explores the methods and tools used to identify, evaluate, and mitigate IoT security risks within smart healthcare environments. By reviewing traditional risk modeling techniques, modern AI-driven approaches, and emerging technologies like blockchain and federated learning, the paper offers a holistic perspective on securing smart healthcare infrastructure. It also highlights the importance of compliance with healthcare regulations and the alignment of security practices with clinical workflows. Ultimately, this work seeks to empower healthcare professionals, IT administrators, and policymakers with the knowledge needed to build more secure, resilient, and trustworthy IoT-enabled healthcare ecosystems.
DOI: https://doi.org/10.5281/zenodo.16751572
