Healthcare IoT

Wireless implanted medical devices (WIMD) help millions of device users experience a better quality of life. Because of their life-saving benefits, the devices are experiencing a dramatic growth in usage, application, and complexity. Yet, the rapid growth has precipitated an increase in cybersecurity risks and threats to the devices.  The literature posited that WIMD cybersecurity is a shared responsibility among manufacturers, healthcare providers, and patients.  What is not clear is what role a patient should play in WIMD cybersecurity and how a patient can assume such a role. The multiple case study examined: How are the cybersecurity risks and threats related to WIMDs being communicated to patients who have or will have these devices implanted in their bodies?  The population was cardiac device specialists at surgical hospitals and medical centers across the United States. The sample included 16 cardiac device specialists in the United States, each possessing at least one year of experience working with WIMD patients using in-home cardiac device monitoring systems. By using semistructured interviews with expert cardiac device specialists, the ideas, experiences, and perceptions of healthcare professionals responsible for the cybersecurity awareness and education of WIMD patients were examined. Through thematic analysis (TA), results yielded five themes: (a) the influence of the media on patient cybersecurity awareness, (b) the need for risk/benefit analysis at all levels of patient interaction, (c) a culture of noncommunication in the healthcare field and the medical device industry, (d) the need for collaboration and education among manufacturers, providers, and patients, and (e) the obstacles and challenges present in all phases of patient care.  Information gathered from healthcare professionals who worked intimately with the highly vulnerable WIMD patient population (cardiac device patients) provided valuable insights for medical device manufacturers, healthcare providers, policymakers, and patients across the WIMD macrocosm.  The research contributes scientific data to the body of knowledge in the field of WIMD cybersecurity and assists scholars and practitioners in advancing education and research in the field of healthcare cybersecurity.

Internet of things (IoT) has emerged as a topic of intense interest among the research and industrial community since it created a revolutionary impact on human life. The rapid growth of IoT technology has revolutionized human life by inaugurating the concept of smart devices, smart healthcare, smart industry, smart city, smart grid, among others. IoT devices' security has become a serious concern nowadays, especially for the healthcare domain, where recent attacks exposed damaging IoT security vulnerabilities. Traditional network security solutions are well established. However, due to the resource constraint property of IoT devices and the distinct behavior of IoT protocols, the existing security mechanisms cannot be deployed directly for securing the IoT devices and network from cyber-attacks. To enhance the level of security for IoT, researchers need IoT-specific tools, methods, and datasets. To address the mentioned problem, we provide a framework for developing IoT context-aware security solutions to detect malicious traffic in IoT use cases. The proposed framework consists of a newly created, open-source IoT data generator tool named IoT-Flock. The IoT-Flock tool allows researchers to develop an IoT use-case comprised of both normal and malicious IoT devices and generate traffic. Additionally, the proposed framework provides an open-source utility for converting the captured traffic generated by IoT-Flock into an IoT dataset. Using the proposed framework in this research, we first generated an IoT healthcare dataset which is comprised of both normal and IoT attack traffic. Afterwards, we applied different machine learning techniques to the generated dataset to detect the cyber-attacks and protect the healthcare system from cyber-attacks. The proposed framework will help in developing the context-aware IoT security solutions, especially for a sensitive use case like IoT healthcare environment.

The Internet of things (IoT) has emerged as a topic of intense interest among the research and industrial community as it has had a revolutionary impact on human life. The rapid growth of IoT technology has revolutionized human life by inaugurating the concept of smart devices, smart healthcare, smart industry, smart city, smart grid, among others. IoT devices’ security has become a serious concern nowadays, especially for the healthcare domain, where recent attacks exposed damaging IoT security vulnerabilities. Traditional network security solutions are well established. However, due to the resource constraint property of IoT devices and the distinct behavior of IoT protocols, the existing security mechanisms cannot be deployed directly for securing the IoT devices and network from the cyber-attacks. To enhance the level of security for IoT, researchers need IoT-specific tools, methods, and datasets. To address the mentioned problem, we provide a framework for developing IoT contex...

The COVID-19 pandemic drastically changed our way of living. To minimize life losses, multi-level strategies requiring collective efforts were adopted while waiting for the vaccines' rollout. The management of such complex processes has taken benefit from the rising framework of the Internet of Things (IoT), and particularly the Radiofrequency Identification (RFID) since it is probably the most suitable approach to both the micro (user) and the macro (processes) scale. Hence, a single infrastructure can support both the logistic and monitoring issues related to the war against a pandemic. Based on the COVID-19 experience, this paper is a survey on how state-of-the-art RFID systems can be employed in facing future pandemic outbreaks. The three pillars of the contrast of the pandemic are addressed: 1) use of Personal Protective Equipment (PPE), 2) access control and social distancing, and 3) early detection of symptoms. For each class, the envisaged RFID devices and procedures are discussed based on the available technology and the current worldwide research. This survey that RFID could generate an extraordinary amount of data so that complementary paradigms of Edge Computing and Artificial intelligence can be tightly integrated to extract profiles and identify anomalous events in compliance with privacy and security.

This book provides in depth knowledge about critical factors involved in the success of pervasive healthcare. The book first presents critical components and importance of pervasive healthcare. The authors then give insight into the pervasive healthcare information systems and key consideration related to remote patient monitoring and safety. The book provides in-depth discussion about the security issues and protocols for pervasive healthcare. This book explores concepts and techniques behind the successive pervasive healthcare systems by providing in-depth knowledge about patient empowerment, remote patient monitoring, network establishment and protocols for effective pervasive healthcare. The book also provides case studies in the field. It is an ideal resource for researchers, students and healthcare organizations to get insight about the state of the art in pervasive healthcare systems.

Provides current research, developments, and applications in pervasive healthcare;
Includes technologies such as machine learning, cryptography, fog computing, and big data in the advancement of e-healthcare;
Pertinent for researchers, students, practitioners and healthcare decision makers.