About this Research Topic
The healthcare sector has increasingly embraced electronic health records (EHR), medical technologies, and the Internet of Things (IoT) to enhance the efficiency and quality of healthcare services. This has given rise to the Internet of Medical/Health Things (IoMT/IoHT) and the adoption of telemedicine and remote healthcare services, particularly in response to the COVID-19 pandemic. While these advancements provide convenient solutions for remote healthcare delivery, they also introduce new cybersecurity considerations and vulnerabilities for healthcare institutions, making cybersecurity a critical concern. Malicious actors target healthcare networks due to the valuable data they contain and the inadequate cybersecurity defenses in place, compromising patient data confidentiality, integrity, and availability, disrupting medical services, and jeopardizing patient safety. Robust cybersecurity measures and frameworks are essential to prevent cyber attacks in healthcare systems.
Despite efforts to address these challenges, significant obstacles persist in areas such as big data analytics, exploration of blockchain technology, standardization, and regulatory compliance. Healthcare organizations must prioritize educating and training their staff in cybersecurity best practices, fostering cyber-aware environments, and ensuring the confidentiality and trustworthiness of healthcare solutions. Implementing risk management strategies to assess the safety and security of medical devices and systems is crucial. Proposed approaches aim to improve cybersecurity and mitigate the risks of intelligent and advanced cyber attacks. However, further research and development are needed to enhance healthcare system cybersecurity and safeguard patient data privacy and safety. Compliance with regulatory requirements and frameworks for healthcare cybersecurity, as well as certification schemes, are essential, as well as education and training of staff in cybersecurity best practices.
This Research Topic focuses on recent advancements in critical cybersecurity measures, including but not limited to technologies such as artificial intelligence (AI), machine learning (ML), and blockchain technology. The objective is to explore how these technologies can be applied in proposed architectures and infrastructures to address data validation, ensure the authenticity of data and receivers, detect attacks, and secure AI algorithms and applications. It also emphasizes the need for authentication and access control at a large scale and examines the potential impact of GenerativeAI on efficiency, security, and the implementation of mitigation measures. This Research Topic also explores the utilization of next-generation firewalls to detect and block advanced persistent threats (APTs), vulnerability assessment tools and procedures to identify and mitigate security weaknesses, and the implementation of digital twins for simulating and testing the effectiveness of cybersecurity measures. Healthcare frameworks should prioritize device certification against standardized vulnerabilities and authenticate healthcare services to prevent unauthorized access to sensitive data. The emergence of EHR standards and distribution formats such as the Fast Healthcare Interoperability Resources (FHIR) adds a critical perspective to this research, given its current momentum and implications on future security strategies. Considering the substantial volume and accessibility of data within the healthcare sector, establishing secure and scalable mechanisms for data sharing is of utmost importance, warranting comprehensive investigation and analysis in this Research Topic.
This Research Topic aims to compile and examine the current state of the art in emerging cybersecurity solutions, focusing on their developments, issues, and challenges. We invite original, unpublished, and novel research submissions that provide in-depth exploration and contribute significantly to the field in terms of methodology or application. We welcome a range of article types, including reviews, case studies, commentaries, theoretical works, and perspectives.
Despite efforts to address these challenges, significant obstacles persist in areas such as big data analytics, exploration of blockchain technology, standardization, and regulatory compliance. Healthcare organizations must prioritize educating and training their staff in cybersecurity best practices, fostering cyber-aware environments, and ensuring the confidentiality and trustworthiness of healthcare solutions. Implementing risk management strategies to assess the safety and security of medical devices and systems is crucial. Proposed approaches aim to improve cybersecurity and mitigate the risks of intelligent and advanced cyber attacks. However, further research and development are needed to enhance healthcare system cybersecurity and safeguard patient data privacy and safety. Compliance with regulatory requirements and frameworks for healthcare cybersecurity, as well as certification schemes, are essential, as well as education and training of staff in cybersecurity best practices.
This Research Topic focuses on recent advancements in critical cybersecurity measures, including but not limited to technologies such as artificial intelligence (AI), machine learning (ML), and blockchain technology. The objective is to explore how these technologies can be applied in proposed architectures and infrastructures to address data validation, ensure the authenticity of data and receivers, detect attacks, and secure AI algorithms and applications. It also emphasizes the need for authentication and access control at a large scale and examines the potential impact of GenerativeAI on efficiency, security, and the implementation of mitigation measures. This Research Topic also explores the utilization of next-generation firewalls to detect and block advanced persistent threats (APTs), vulnerability assessment tools and procedures to identify and mitigate security weaknesses, and the implementation of digital twins for simulating and testing the effectiveness of cybersecurity measures. Healthcare frameworks should prioritize device certification against standardized vulnerabilities and authenticate healthcare services to prevent unauthorized access to sensitive data. The emergence of EHR standards and distribution formats such as the Fast Healthcare Interoperability Resources (FHIR) adds a critical perspective to this research, given its current momentum and implications on future security strategies. Considering the substantial volume and accessibility of data within the healthcare sector, establishing secure and scalable mechanisms for data sharing is of utmost importance, warranting comprehensive investigation and analysis in this Research Topic.
This Research Topic aims to compile and examine the current state of the art in emerging cybersecurity solutions, focusing on their developments, issues, and challenges. We invite original, unpublished, and novel research submissions that provide in-depth exploration and contribute significantly to the field in terms of methodology or application. We welcome a range of article types, including reviews, case studies, commentaries, theoretical works, and perspectives.
Keywords: Cybersecurity, Healthcare, Artificial Intelligence, Machine Learning, Internet of Things, Internet of Medical Things, Telemedicine
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
