Lightweight Mutual Authentication Scheme Based on Blockchain for Internet of Medical Things

To address the issues of poor user privacy protection and insecure communication in the Internet of Medical Things (IoMT) environment, we propose a blockchain-based lightweight mutual authentication scheme for the IoMT. First, our scheme is a two-factor authentication scheme that uses certificates and feature information for identity authentication. Second, we use elliptic curve cryptography and the Chinese remainder theorem to design a lightweight identity registration and authentication algorithm. This algorithm can aggregate multiple identity information of users for verification, while achieving efficient user identity authentication and ensuring the security of user identity information. Finally, we combined nonfungible tokens (NFTs) with user device information, and through a composable NFT solution, we ensured the uniqueness and immutability of user identity information on the blockchain, while facilitating user identity management. The formal security analysis based on AVISPA has proven the security of our scheme. Performance analysis shows that the proposed scheme has low communication and storage overhead. We simulated the proposed scheme on the Ethereum platform using the Solidity language and conducted latency and throughput analysis of our smart contracts using the stress testing tool, Hyperledger Caliper. The results illustrate the practicality of our scheme.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-11-20
DOI
https://doi.org/10.1109/jiot.2024.3503065
Citations
7
Primary Topic
Advanced Authentication Protocols Security
Type
article
Field-Weighted Citation Impact
2.44

Funders

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article

Lightweight Mutual Authentication Scheme Based on Blockchain for Internet of Medical Things

Xiaoqiang Di, Makram Ibrahim, Xusheng Li, Shi Qiu et al.
7 citations
IEEE Internet of Things Journal
Advanced Authentication Protocols Security
2.44
article

Lightweight Mutual Authentication Scheme Based on Blockchain for Internet of Medical Things

Xiaoqiang Di, Makram Ibrahim, Xusheng Li, Shi Qiu, Wu Yunlong, Jinqing Li
article en
7 citations

Abstract

To address the issues of poor user privacy protection and insecure communication in the Internet of Medical Things (IoMT) environment, we propose a blockchain-based lightweight mutual authentication scheme for the IoMT. First, our scheme is a two-factor authentication scheme that uses certificates and feature information for identity authentication. Second, we use elliptic curve cryptography and the Chinese remainder theorem to design a lightweight identity registration and authentication algorithm. This algorithm can aggregate multiple identity information of users for verification, while achieving efficient user identity authentication and ensuring the security of user identity information. Finally, we combined nonfungible tokens (NFTs) with user device information, and through a composable NFT solution, we ensured the uniqueness and immutability of user identity information on the blockchain, while facilitating user identity management. The formal security analysis based on AVISPA has proven the security of our scheme. Performance analysis shows that the proposed scheme has low communication and storage overhead. We simulated the proposed scheme on the Ethereum platform using the Solidity language and conducted latency and throughput analysis of our smart contracts using the stress testing tool, Hyperledger Caliper. The results illustrate the practicality of our scheme.

IEEE Internet of Things JournalVol. 12(7)
Changchun University of Science and Technology (CN), National Research Institute of Astronomy and Geophysics (EG), Changchun Institute of Technology (CN)
Natural Science Foundation of Chongqing, Jilin Scientific and Technological Development Program
Openalex Percentile: Top 10%
Advanced Authentication Protocols Security
2.44
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Lightweight Mutual Authentication Scheme Based on Blockchain for Internet of Medical Things — Xiaoqiang Di, Makram Ibrahim, et al. · IEEE Internet of Things Journal (2024) | TGRS Research Map | TGRS