Lightweight and expressive fine-grained access control for healthcare internet-of-things
Healthcare Internet-of-Things (IoT) is an emerging paradigm that enables embedded devices to monitor patients vital signals and allows these data to be aggregated and outsourced to the cloud. The cloud enables authorized users to store and share data to enjoy on-demand services. Nevertheless, it als...
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sg-smu-ink.sis_research-82522022-10-13T02:57:04Z Lightweight and expressive fine-grained access control for healthcare internet-of-things XU, Shengmin Li, Yingjiu DENG, Robert H. ZHANG, Yinghui LUO, Xiangyang LIU, Ximeng Healthcare Internet-of-Things (IoT) is an emerging paradigm that enables embedded devices to monitor patients vital signals and allows these data to be aggregated and outsourced to the cloud. The cloud enables authorized users to store and share data to enjoy on-demand services. Nevertheless, it also causes many security concerns because of the untrusted network environment, dishonest cloud service providers and resource-limited devices. To preserve patients' privacy, existing solutions usually apply cryptographic tools to offer access controls. However, fine-grained access control among authorized users is still a challenge, especially for lightweight and resource-limited end-devices. In this paper, we propose a novel healthcare IoT system fusing advantages of attribute-based encryption, cloud and edge computing, which provides an efficient, flexible, secure fine-grained access control mechanism with data verification in healthcare IoT network without any secure channel and enables data users to enjoy the lightweight decryption. We also define the formal security models and present security proofs for our proposed scheme. The extensive comparison and experimental simulation demonstrate that our scheme has better performance than existing solutions. 2022-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7249 info:doi/10.1109/TCC.2019.2936481 https://ink.library.smu.edu.sg/context/sis_research/article/8252/viewcontent/LightweightExpressiveFine_Grained_2022_av.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Internet-of-Things access control cloud computing edge computing attribute-based encryption Health Information Technology Information Security |
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Internet-of-Things access control cloud computing edge computing attribute-based encryption Health Information Technology Information Security XU, Shengmin Li, Yingjiu DENG, Robert H. ZHANG, Yinghui LUO, Xiangyang LIU, Ximeng Lightweight and expressive fine-grained access control for healthcare internet-of-things |
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Healthcare Internet-of-Things (IoT) is an emerging paradigm that enables embedded devices to monitor patients vital signals and allows these data to be aggregated and outsourced to the cloud. The cloud enables authorized users to store and share data to enjoy on-demand services. Nevertheless, it also causes many security concerns because of the untrusted network environment, dishonest cloud service providers and resource-limited devices. To preserve patients' privacy, existing solutions usually apply cryptographic tools to offer access controls. However, fine-grained access control among authorized users is still a challenge, especially for lightweight and resource-limited end-devices. In this paper, we propose a novel healthcare IoT system fusing advantages of attribute-based encryption, cloud and edge computing, which provides an efficient, flexible, secure fine-grained access control mechanism with data verification in healthcare IoT network without any secure channel and enables data users to enjoy the lightweight decryption. We also define the formal security models and present security proofs for our proposed scheme. The extensive comparison and experimental simulation demonstrate that our scheme has better performance than existing solutions. |
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text |
author |
XU, Shengmin Li, Yingjiu DENG, Robert H. ZHANG, Yinghui LUO, Xiangyang LIU, Ximeng |
author_facet |
XU, Shengmin Li, Yingjiu DENG, Robert H. ZHANG, Yinghui LUO, Xiangyang LIU, Ximeng |
author_sort |
XU, Shengmin |
title |
Lightweight and expressive fine-grained access control for healthcare internet-of-things |
title_short |
Lightweight and expressive fine-grained access control for healthcare internet-of-things |
title_full |
Lightweight and expressive fine-grained access control for healthcare internet-of-things |
title_fullStr |
Lightweight and expressive fine-grained access control for healthcare internet-of-things |
title_full_unstemmed |
Lightweight and expressive fine-grained access control for healthcare internet-of-things |
title_sort |
lightweight and expressive fine-grained access control for healthcare internet-of-things |
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Institutional Knowledge at Singapore Management University |
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2022 |
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https://ink.library.smu.edu.sg/sis_research/7249 https://ink.library.smu.edu.sg/context/sis_research/article/8252/viewcontent/LightweightExpressiveFine_Grained_2022_av.pdf |
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