Aug 2026· Sri Lankan Journal of Technology· 0 citations
TL;DR
A thorough study of 41 peer-reviewed research papers from January 2018 through May 2025 revealed the current state of security vulnerabilities and resilience strategies in healthcare IoT systems and provides a comprehensive analysis of security threats at the device, network, and application levels.
Abstract
Internet of Things (IoT) technologies in the healthcare industry, also known as the Internet of Medical Things (IoMT), have proven to greatly improve patient monitoring, diagnostics, and clinical decision-making. The increasing prevalence of resource-challenged medical devices, wireless connectivity, and cloud services, however, has brought new risks around security and privacy concerns that can now directly impact patient safety and data integrity. In this paper, a thorough study of 41 peer-reviewed research papers from January 2018 through May 2025 revealed the current state of security vulnerabilities and resilience strategies in healthcare IoT systems. It provides a comprehensive analysis of security threats at the device, network, and application levels such as unauthorized access, malware and ransomware, data breaches, and denial-of-service attacks delivered in a systematic manner. This contrasts with existing surveys, which consider single security mechanisms and improve upon various multi-layered security means such as AI-enabled anomaly detection, blockchain-based authentication and auditability, low-compute cryptographic techniques, and privacy-preserving methods such as federated learning. The outcomes also show that although emerging technologies add a great deal of security and trust capabilities, issues on scalability, interoperability, deployment, and regulations are not yet fully addressed. This review highlights important knowledge gaps and offers structured knowledge and future directions for research to address the design of secure, resilient, and practically deployable IoMT architectures for real-world healthcare environments.
It is suggested that scalable smart home security requires coordinated progress in protocol standardization, enforceable device update lifecycles, gateway-level anomaly detection, and privacy-preserving local analytics rather than reliance on a single technical solution.
Dalibor Radovanovic, Nikola Savanović, Jelena Janackovic et al.· Big Data and Cognitive Compu...· 0 citations
Background: The application of the Internet of Things (IoT) in healthcare has allowed continuous patient surveillance, data acquisition, and analytics for better patient care. However, the amount of healthcare data generated by IoT devices has created several security and privacy concerns related to information’s confidentiality, integrity, and scalability in the health care system. Problem Statement: The current healthcare system lacks mechanisms to ensure data confidentiality, integrity, and effective monitoring of real-time patient statistics while providing efficient and effective healthcare services. In addition, the conventional security measures may not be sufficient to detect various forms of attacks in a real-time healthcare IoT environment.
Purpose: This paper proposes an efficient and reliable healthcare framework that addresses several IoT-related security issues while ensuring confidentiality and integrity of health data and providing effective anomaly detection. Methods: The study presents a framework that uses a combination of IoT, blockchain, artificial intelligence, and neural-enhanced encryption to offer a more secure and reliable healthcare system. It utilizes neural networks to provide encryption and implement an anomaly detection model that uses a hybrid long short-term memory autoencoder and support vector machine detecting abnormal physiological observations in IoT-generated healthcare data. In addition, the framework uses a modified proof-of-authority consensus algorithm to ensure faster transaction validation and reliable processing in a permissioned blockchain network. The framework has been tested using simulated healthcare IoT networks with 150, 600, and 1200 nodes and a database with 1200 patient records. Results: The proposed framework achieved an anomaly detection accuracy of 98.99% with 0.89 precision, 0.93 recall, and 0.91 F1-Score. Besides, the framework detected 95% of the attacks and maintained optimal performance in the networks with varying node numbers. Conclusion: The study revealed that the combination of IoT, blockchain, intelligent anomaly detection, and neural-enhanced encryption could be an efficient and reliable solution to the current health care issues. The proposed framework offers several benefits, including improved confidentiality and integrity of health data, improved attack detection, and efficient and effective processing of transactions in a permissioned blockchain network.
Tanishka Pahwa, G. Bawa· International Journal of App...· 0 citations
Cyber-Physical Systems (CPS), a combination of embedded computing, communication networks, and physical processes, are increasingly reshaping clinical practice, pharmaceutical supply chains, and hospital infrastructure. This review covers key principles of Medical CPS design; major interoperability frameworks such as FHIR (Fast Healthcare Interoperability Resources), IEEE 11073, and DICOM; and critical cybersecurity risks that threaten patient safety and data integrity, including ransomware, man-in-the-middle, denial-of-service, and data injection attacks. A review of the literature from 2020 to the present (2025) shows that architectural fragmentation has continued, that there is a lack of harmonised security-by-design standards, and that there is a lack of regulatory guidance on real-time MCPS deployments. Some promising mitigation strategies, such as blockchain-based trust frameworks, AI-powered intrusion detection, and digital twin validation, are introduced. The papers conclusion recommends a research agenda for interoperability protocols, context-aware security models, and international regulatory convergence as essential factors for implementing safe and scalable MCPS.
Emmanuel Nkansah, M. Oladosu, M. Abah et al.· International Journal of Pre...· 0 citations
The ways in which artificial intelligence, blockchain technology, edge computing, and Zero Trust Architecture will transform IoT security paradigms are examined, which will reveal long-standing issues such as resource limitations, device heterogeneity, and scaling challenges.
Muhammad Sami Intizar, Maria Sikandar, Aqsa Siddique et al.· Journal of Computational and...· 0 citations
It is argued that securing the IoT ecosystem requires sustained, coordinated effort from manufacturers, regulators and end-users, and where current technological and regulatory responses fall short of that goal is identified.
K. Curran, J. Kyle, Lovepreet Singh· Recent Progress in Science a...· 0 citations
This work proposes an intelligent, lightweight Tiny LSTM–GRU hybrid IDS on the edge to monitor device-generated behavioral patterns in real time, with minimal computational and energy overhead, and proposes an adaptive FedProx-based weighted federated learning framework.
Emmanuel Udok, B. Stephen, U. Luke et al.· E3S Web of Conferences· 0 citations
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