Secure online/offline data sharing framework for cloud-assisted industrial internet of things
Ciphertext-policy attribute-based keyword search (CP-ABKS) schemes facilitate the fine-grained keyword search over encrypted data, such as those sensed/collected from Industrial Internet of Things (IIoT) devices and stored in the cloud. However, existing CP-ABKS schemes generally have significant co...
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sg-smu-ink.sis_research-55272019-12-19T04:00:06Z Secure online/offline data sharing framework for cloud-assisted industrial internet of things MIAO, Yinbin TONG, Qiuyun CHOO, Kim-Kwang Raymond LIU, Ximeng DENG, Robert H. LI, Hongwei Ciphertext-policy attribute-based keyword search (CP-ABKS) schemes facilitate the fine-grained keyword search over encrypted data, such as those sensed/collected from Industrial Internet of Things (IIoT) devices and stored in the cloud. However, existing CP-ABKS schemes generally have significant computation and storage requirements, which are beyond those of resource-constrained IIoT devices. Therefore, in this paper, we design a secure online/offline data sharing framework (DSF), which supports online/offline encryption and outsourced decryption. Using the healthcare setting as a case study, we demonstrate how DSF can be deployed in the cloud-assisted Healthcare IIoT (HealthIIoT) system. We not only prove that the DSF is selectively secure in the chosen access structure security model but also demonstrate its efficiency and feasibility in practical scenarios using experiments. 2019-06-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/4524 info:doi/10.1109/JIOT.2019.2923068 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Encryption Medical services Internet of Things Keyword search Access control Cloud computing Information Security |
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Encryption Medical services Internet of Things Keyword search Access control Cloud computing Information Security MIAO, Yinbin TONG, Qiuyun CHOO, Kim-Kwang Raymond LIU, Ximeng DENG, Robert H. LI, Hongwei Secure online/offline data sharing framework for cloud-assisted industrial internet of things |
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Ciphertext-policy attribute-based keyword search (CP-ABKS) schemes facilitate the fine-grained keyword search over encrypted data, such as those sensed/collected from Industrial Internet of Things (IIoT) devices and stored in the cloud. However, existing CP-ABKS schemes generally have significant computation and storage requirements, which are beyond those of resource-constrained IIoT devices. Therefore, in this paper, we design a secure online/offline data sharing framework (DSF), which supports online/offline encryption and outsourced decryption. Using the healthcare setting as a case study, we demonstrate how DSF can be deployed in the cloud-assisted Healthcare IIoT (HealthIIoT) system. We not only prove that the DSF is selectively secure in the chosen access structure security model but also demonstrate its efficiency and feasibility in practical scenarios using experiments. |
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text |
author |
MIAO, Yinbin TONG, Qiuyun CHOO, Kim-Kwang Raymond LIU, Ximeng DENG, Robert H. LI, Hongwei |
author_facet |
MIAO, Yinbin TONG, Qiuyun CHOO, Kim-Kwang Raymond LIU, Ximeng DENG, Robert H. LI, Hongwei |
author_sort |
MIAO, Yinbin |
title |
Secure online/offline data sharing framework for cloud-assisted industrial internet of things |
title_short |
Secure online/offline data sharing framework for cloud-assisted industrial internet of things |
title_full |
Secure online/offline data sharing framework for cloud-assisted industrial internet of things |
title_fullStr |
Secure online/offline data sharing framework for cloud-assisted industrial internet of things |
title_full_unstemmed |
Secure online/offline data sharing framework for cloud-assisted industrial internet of things |
title_sort |
secure online/offline data sharing framework for cloud-assisted industrial internet of things |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2019 |
url |
https://ink.library.smu.edu.sg/sis_research/4524 |
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1770574883664691200 |