Hybrid keyword-field search with efficient key management for industrial Internet of Things
Equipped with the emerging cloud computing, clients prefer to outsource the increasing number of Industrial Internet of things (IIoT) data to cloud to reduce the high storage and computation burden. However, existing searchable encryption (SE) schemes just apply to IIoT records containing textual ke...
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sg-smu-ink.sis_research-56782020-01-02T06:18:03Z Hybrid keyword-field search with efficient key management for industrial Internet of Things MIAO, Yinbin LIU, Ximeng DENG, Robert H. WU, Hongjun LI, Hongwei LI, Jiguo WU. Dapeng, Equipped with the emerging cloud computing, clients prefer to outsource the increasing number of Industrial Internet of things (IIoT) data to cloud to reduce the high storage and computation burden. However, existing searchable encryption (SE) schemes just apply to IIoT records containing textual keyword fields rather than both digital and textual keyword ones. Besides, the key management issue still impedes the practicality and availability of SE schemes due to high key storage overhead. To this end, we present an outsourced Hybrid Keyword-Field Search over encrypted data with efficient Keys Management (HKFS-KM) scheme by utilizing the relevance score function and keyed hash tree. Formal security analysis proves that the HKFS-KM scheme can achieve keyword privacy and trapdoor unlinkability in both known ciphertexts attack model and known background attack model. Experimental results using real-world dataset show its efficiency and practicality in practice. 2019-06-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/4675 info:doi/10.1109/TII.2018.2877146 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Information Security |
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Information Security MIAO, Yinbin LIU, Ximeng DENG, Robert H. WU, Hongjun LI, Hongwei LI, Jiguo WU. Dapeng, Hybrid keyword-field search with efficient key management for industrial Internet of Things |
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Equipped with the emerging cloud computing, clients prefer to outsource the increasing number of Industrial Internet of things (IIoT) data to cloud to reduce the high storage and computation burden. However, existing searchable encryption (SE) schemes just apply to IIoT records containing textual keyword fields rather than both digital and textual keyword ones. Besides, the key management issue still impedes the practicality and availability of SE schemes due to high key storage overhead. To this end, we present an outsourced Hybrid Keyword-Field Search over encrypted data with efficient Keys Management (HKFS-KM) scheme by utilizing the relevance score function and keyed hash tree. Formal security analysis proves that the HKFS-KM scheme can achieve keyword privacy and trapdoor unlinkability in both known ciphertexts attack model and known background attack model. Experimental results using real-world dataset show its efficiency and practicality in practice. |
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text |
author |
MIAO, Yinbin LIU, Ximeng DENG, Robert H. WU, Hongjun LI, Hongwei LI, Jiguo WU. Dapeng, |
author_facet |
MIAO, Yinbin LIU, Ximeng DENG, Robert H. WU, Hongjun LI, Hongwei LI, Jiguo WU. Dapeng, |
author_sort |
MIAO, Yinbin |
title |
Hybrid keyword-field search with efficient key management for industrial Internet of Things |
title_short |
Hybrid keyword-field search with efficient key management for industrial Internet of Things |
title_full |
Hybrid keyword-field search with efficient key management for industrial Internet of Things |
title_fullStr |
Hybrid keyword-field search with efficient key management for industrial Internet of Things |
title_full_unstemmed |
Hybrid keyword-field search with efficient key management for industrial Internet of Things |
title_sort |
hybrid keyword-field search with efficient key management for industrial internet of things |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2019 |
url |
https://ink.library.smu.edu.sg/sis_research/4675 |
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1770574961825546240 |