A Conceptual Model for Internet of Things Risk Assessment in Healthcare Domain with Deep Learning Approach Article Swipe
Mohd Nizam Zakaria
,
Nur Azaliah Abu Bakar
,
Hafiza Abas
,
Noor Hafizah Hassan
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.11113/ijic.v10n2.263
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.11113/ijic.v10n2.263
The Internet of Things (IoT) has become a prevalent technology in the IT industry. One of the industries that can benefit extensively in this technology is healthcare. However, the healthcare IoT is still under debate with several studies suggesting it is lack of interoperability, security, and too much complexity. Even more, the risk involved in deploying it is still enormous. Many traditional risk assessment models are unable to provide a specific IoT risk guideline and specification, especially in the healthcare area. Thus, it is essential to understand the full extent of the IoT risk and how to manage its risk in the healthcare area. The risk management models, such as NIST SP 800-30, ISO/IEC 27005, OCTAVE, CRAMM, and EBIOS, which are among the leading and widely used in many areas and healthcare fields, have also been described. Besides, this paper includes a review of three IoT risk assessment models that are based on ABA-IDS, Deep Learning, and AHP-SVM. Based on the review analysis, we proposed a new enhanced healthcare IoT risk assessment model, which aims to provide a real-time monitoring and mitigating risks that incorporate the NIST SP 800-30 framework, ABA-IDS, and CNN deep learning. This shall constitute a better classification of each risk identified to find the best risk mitigation plan.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.11113/ijic.v10n2.263
- OA Status
- diamond
- Cited By
- 3
- References
- 20
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W3107556155Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.11113/ijic.v10n2.263Digital Object Identifier
- Title
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A Conceptual Model for Internet of Things Risk Assessment in Healthcare Domain with Deep Learning ApproachWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-11-19Full publication date if available
- Authors
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Mohd Nizam Zakaria, Nur Azaliah Abu Bakar, Hafiza Abas, Noor Hafizah HassanList of authors in order
- Landing page
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https://doi.org/10.11113/ijic.v10n2.263Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.11113/ijic.v10n2.263Direct OA link when available
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Interoperability, Computer science, Health care, Risk assessment, Risk analysis (engineering), Risk management, NIST, Healthcare industry, Data science, Computer security, Artificial intelligence, Business, World Wide Web, Economic growth, Economics, Finance, Natural language processingTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
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2025: 1, 2023: 1, 2021: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| publication_year | 2020 |
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