ABSTRACT
Telemedicine and telehealth care system show the revolutionary and modern way to deal with the coronavirus 2019 pandemic. However, such systems are facing increased security risks. As a result, healthcare providers and academic institutions must be well-informed, safe, and prepared to respond to any cyber-attack. The aim of this paper is to conduct a review of healthcare information systems together with how security can be provided for such systems. The paper main focus is on the adoption of blockchain technology to support the security of the healthcare system. This adoption has been investigated and assessed to show its benefits compared with other conventional technologies. Finally, a recommendation was pointed out for the security of healthcare with the usage of blockchain technology. © 2022 IEEE.
ABSTRACT
The future of the healthcare sector and its systems are beginning to take shape by combining technological innovations with traditional techniques to generate new and efficient solutions for patient care and data storage. Most conventional medical information management and storage systems are centralized, which means there is a risk of data loss in the event of malicious attacks or even natural disasters because of the single point of failure that centralized systems have. Blockchain technology is decentralized and emerging, offering the potential to significantly revolutionize how data is stored and managed in the healthcare industry. This paper presents the advantages of using blockchain in the healthcare sector, as this technology has a strategic role in both the management of stored data and the creation of predictive systems that could prevent a pandemic like the one generated by the SARS-Cov-2 virus. We present different existing studies and the method addressed in the ongoing STAMINA project. © 2022 IEEE.
ABSTRACT
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 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 comprises 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.