SLMAS: A Secure and Light Weight Mutual Authentication Scheme for the Smart Wheelchair Article Swipe
YOU?
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· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/app13116564
The modern innovation called the Internet of Things (IoT) empowers individuals to connect to anybody and anything at any point, wherever. The application of the IoT in smart cities concerning smart healthcare management can improve patient welfare, user acceptance, the standard of living, and accurate illness monitoring. Powered wheelchairs (PW) with sensors, computers, and other connected assistive technologies are called smart wheelchairs. Smart wheelchairs with sensing abilities are intended to offer universal connectivity using cloud and edge computing technology. Numerous outstanding people were impacted by paralyzing phenomena, including Stephen Hawking and Max Brito. The issue of legitimacy is one of the most important difficulties in e-health applications, because of how sensitive the technology is, and this needs to be appropriately handled. To safeguard the data transport, usage, and interchange between sensor nodes/smart wheelchairs and servers, e-health applications require an authentication method. As all conversations use wireless channels, e-health apps are exposed to various vulnerabilities. Additionally, the IoT has limited computational and power capacity limitations. To combat the various security risks, the present research offers a user authentication technique that is efficient and ensures anonymity. The suggested method creates a safe connection for the authorized entity and forbids unauthorized entities from accessing the Internet of Things sensor nodes. The suggested approach has lower communication and computation overheads than the traditional techniques, making it more effective. In addition, the security verification of the presented protocol is scrutinized through AVISPA. The proposed scheme, on average, requires only 12.4% more computation cost to execute. Compared to the existing approaches, the suggested protocol’s extra computational cost can be compensated for by its enhanced security, while the suggested method’s communication cost is 46.3% smaller.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app13116564
- https://www.mdpi.com/2076-3417/13/11/6564/pdf?version=1685342667
- OA Status
- gold
- Cited By
- 3
- References
- 53
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4378619539
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4378619539Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/app13116564Digital Object Identifier
- Title
-
SLMAS: A Secure and Light Weight Mutual Authentication Scheme for the Smart WheelchairWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-05-28Full publication date if available
- Authors
-
Abdulwahab Ali Almazroi, Misbah Liaqat, Rana Liaqat Ali, Abdullah GaniList of authors in order
- Landing page
-
https://doi.org/10.3390/app13116564Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/13/11/6564/pdf?version=1685342667Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2076-3417/13/11/6564/pdf?version=1685342667Direct OA link when available
- Concepts
-
Computer security, Computer science, Mutual authentication, Anonymity, Authentication (law), Smart objects, Internet of Things, Internet privacyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2Per-year citation counts (last 5 years)
- References (count)
-
53Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5088112660 |
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| corresponding_institution_ids | https://openalex.org/I16076960 |
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| citation_normalized_percentile.is_in_top_10_percent | False |