The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Cloud Centric Authentication for Wearable Healthcare Monitoring System
Abstract
Security and privacy are the major concerns in cloud computing as users have limited access on the stored data at the remote locations managed by different service providers. These become more challenging especially for the data generated from the wearable devices as it is highly sensitive and heterogeneous in nature. Most of the existing techniques reported in the literature are having high computation and communication costs and are vulnerable to various known attacks, which reduce their importance for applicability in real-world environment. Hence, in this paper, we propose a new cloud based user authentication scheme for secure authentication of medical data. After successful mutual authentication between a user and wearable sensor node, both establish a secret session key that is used for future secure communications. The extensively-used Real-Or-Random (ROR) model based formal security analysis and the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool based formal security verification show that the proposed scheme provides the session-key security and protects active attacks. The proposed scheme is also informally analyzed to show its resilience against other known attacks. Moreover, we have done a detailed comparative analysis for the communication and computation costs along with security and functionality features which proves its efficiency in comparison to the other existing schemes of its category.
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Cites
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Cited by
A Survey on Internet of Things and Cloud Computing for Healthcare
Dang, L. M., Piran, M. J., Han, D., Min, K., & Moon, H. (2019) · Electronics · doi:10.3390/electronics8070768 · Cited by 640
An exhaustive survey on security and privacy issues in Healthcare 4.0
Hathaliya, J. J., & Tanwar, S. (2020) · Computer Communications · doi:10.1016/j.comcom.2020.02.018 · Cited by 462
BinDaaS: Blockchain-Based Deep-Learning as-a-Service in Healthcare 4.0 Applications
Bhattacharya, P., Tanwar, S., Bodkhe, U., Tyagi, S., & Kumar, N. (2021) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2019.2961932 · Cited by 284
Self-citationRasool, R. U., Ahmad, H. F., Rafique, W., Qayyum, A., & Qadir, J. (2022) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2022.103332 · Cited by 177
DwaRa: A Deep Learning-Based Dynamic Toll Pricing Scheme for Intelligent Transportation Systems
Shukla, A., Bhattacharya, P., Tanwar, S., Kumar, N., & Guizani, M. (2020) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2020.3022168 · Cited by 41
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Metadata
- Authors
- Srinivas, J., Das, A. K., Kumar, N., & Rodrigues, J. J. P. C.
- Venue
- IEEE Transactions on Dependable and Secure Computing
- Published
- 2020-09-01
- Volume
- 17
- Issue
- 5
- Pages
- 942-956
- ISSN
- 1545-5971 (ISSN-L)
- 1941-0018
- 2160-9209
- OpenAlex
- W2800426337
- Cited by
- 281
- References
- 5
- FWCI
- 18.21
- Type
- journal article
- Language
- en
- Open access
- closed
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