TFAS: two factor authentication scheme for blockchain enabled IoMT using PUF and fuzzy extractor

Singh, Namrata; Das, Ayan

doi:10.1007/s11227-023-05507-6

Cited by 14 publications

(1 citation statement)

References 56 publications

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“…Blockchain has rapidly gained the interest of researchers due to ensuring privacy and interoperability among different health care providers. The authors of Reference 40 proposed a scheme, where a blockchain‐enabled IoMT model using PUF and fuzzy extractor to facilitate security, distributed storage, and scalability, the IPFS technology is used. It provides security at the physical as well as network layer.…”

Section: Background and Related Workmentioning

confidence: 99%

Using smart grid infrastructure for authentication and data management in Internet of Medical Things

Ud Din,

Ali,

Almogren

et al. 2024

Security and Privacy

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The Internet of Medical Things (IoMT) has recently become the norm in medical operations and emergency situations. A physician or a medical personnel is interested in accessing the patients' data from remote locations using IoMT. The patients' medical management system should allow their doctors and family members to have access to the data, especially in emergency situations. Deploying sensor nodes and managing the large amount of medical data generated by these sensors require a system that provides protection against known security threats and a robust mechanism to recover when subjected to attacks. The proposed scheme that provides mutual authentication between user(s) and power generation nodes, and also mitigate against attacks by validating the identity during the authentication phase. Moreover, the proposed scheme, called Grid‐Based Authentication, uses the existing smart grid infrastructure for communications, which is a model of integrated infrastructure in a smart city. Furthermore, the simulation results show that our proposed scheme yields better performance in terms of average throughput, end to end delay, and computation and communication costs compared with other state‐of‐the‐art approaches.

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Section: Background and Related Workmentioning

confidence: 99%