Security of Blockchain and AI-Empowered Smart Healthcare: Application-Based Analysis
Source abstract
Abstract
A smart device carries a great amount of sensitive patient data as it offers innovative and enhanced functionalities in the smart healthcare system. Moreover, the components of healthcare systems are interconnected via the Internet, bringing significant changes to the delivery of healthcare services to individuals. However, easy access to healthcare services and applications has given rise to severe risks and vulnerabilities that hamper the performance of a smart healthcare system. Moreover, a large number of heterogeneous devices accumulate data that vary in terms of size and formats, making it challenging to manage the data in the healthcare repository and secure it from attackers who seek to profit from the data. Thus, smart healthcare systems are susceptible to numerous security threats and risks, such as hardware and software-based attacks, system-level attacks, and network attacks that have the potential to place patients’ lives at risk. An analysis of the literature revealed a research gap in that most security surveys on the healthcare ecosystem examined only the security challenges and did not explore the possibility of integrating modern technologies to alleviate security issues in the smart healthcare system. Therefore, in this article, we conduct a comprehensive review of the various most recent security challenges and their countermeasures in the smart healthcare environment. In addition, an artificial intelligence (AI) and blockchain-based secure architecture is proposed as a case study to analyse malware and network attacks on wearable devices. The proposed architecture is evaluated using various performance metrics such as blockchain scalability, accuracy, and dynamic malware analysis. Lastly, we highlight different open issues and research challenges facing smart healthcare systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Blockchain Technology Applications and Security · IoT and Edge/Fog Computing · Digital Mental Health Interventions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science, College of Computer, Qassim University, Buraydah 52571, Saudi Arabia
Computer Science and Software Engineering, School of Science, RMIT University, Melbourne, VIC 3000, Australia
Funding
Qassim University
References (100+)
Show source-provided references
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