The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Context-Sensitive Access in Industrial Internet of Things (IIoT) Healthcare Applications
Abstract
Industrial Internet of Things (IIoTs) is the fast growing network of interconnected things that collects and exchange data using embedded sensors planted everywhere. Several IIoT applications such as the ones related to healthcare systems are expected to widely utilize the evolving 5G technology. This 5G-inspired IIoT paradigm in healthcare applications enables the users to interact with various types of sensors via secure wireless medical sensor networks (WMSNs). Users of 5G networks should interact with each other in a seamless secure manner. And thus, security richness is highly coveted for the real time wireless sensor network systems. Asking users to verify themselves before every interaction is a tedious, time-consuming process that disrupts inhabitants' activities, and degrades the overall healthcare system performance. To avoid such problems, we propose a context-sensitive seamless identity provisioning (CSIP) framework for the IIoT. CSIP proposes a secure mutual authentication approach using hash and global assertion value to prove that the proposed mechanism can achieve the major security goals of the WMSN in a short time period.
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Cites
1 retracted
Al-Turjman, F. M. (2018) · Computer Communications · doi:10.1016/j.comcom.2018.02.012 · Cited by 55
Self-citationRetractedSensor networks for medical care
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Two-factor user authentication in wireless sensor networks
Das, M. L. (2009) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2008.080128 · Cited by 704
TinyPK: securing sensor networks with public key technology
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Identity-based key agreement protocols from pairings
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A Reconfigurable Smart Sensor Interface for Industrial WSN in IoT Environment
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Cited by
Network Intrusion Detection for IoT Security Based on Learning Techniques
Chaabouni, N., Mosbah, M., Zemmari, A., Sauvignac, C., & Faruki, P. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2896380 · Cited by 940
A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT
Sengupta, J., Ruj, S., & Das Bit, S. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2019.102481 · Cited by 844
Internet of Things (IoT) Cybersecurity Research: A Review of Current Research Topics
Lu, Y., & Xu, L. D. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2869847 · Cited by 567
A systematic review of IoT in healthcare: Applications, techniques, and trends
Haghi Kashani, M., Madanipour, M., Nikravan, M., Asghari, P., & Mahdipour, E. (2021) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103164 · Cited by 491
Tange, K., De Donno, M., Fafoutis, X., & Dragoni, N. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3011208 · Cited by 410
“The Fifth generation cellular network technology (5G) authentication scheme for smart devices proposed in [70] uses Cloud-based learning to dynamically identify and authenticate users based on behavioral patterns, showing another approach for minimizing user interaction.”
Background
Metadata
- Authors
- Al-Turjman, F., & Alturjman, S.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2018-06
- Volume
- 14
- Issue
- 6
- Pages
- 2736-2744
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2792152774
- Cited by
- 264
- References
- 22
- FWCI
- 24.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- Al-Turjman, F., & Alturjman, S. (2018). Context-Sensitive Access in Industrial Internet of Things (IIoT) Healthcare Applications. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2018.2808190
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
