Verifiable online/offline multi-keyword search for cloud-assisted Industrial Internet of Things

Ali, M; Sadeghi, MR; Liu, X; Miao, Y; Vasilakos, AV

Verifiable online/offline multi-keyword search for cloud-assisted Industrial Internet of Things

Ali, M Sadeghi, MR Liu, X Miao, Y Vasilakos, AV

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Journal of Information Security and Applications, 2022, 65, pp. 103101
Issue Date:: 2022-03-01

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Field	Value	Language
dc.contributor.author	Ali, M
dc.contributor.author	Sadeghi, MR
dc.contributor.author	Liu, X
dc.contributor.author	Miao, Y
dc.contributor.author	Vasilakos, AV
dc.date.accessioned	2022-12-07T19:46:58Z
dc.date.available	2022-12-07T19:46:58Z
dc.date.issued	2022-03-01
dc.identifier.citation	Journal of Information Security and Applications, 2022, 65, pp. 103101
dc.identifier.issn	2214-2134
dc.identifier.issn	2214-2126
dc.identifier.uri	http://hdl.handle.net/10453/164208
dc.description.abstract	Attribute-based encryption (ABE) and attribute-based keyword search (ABKS) facilitate fine-grained access and search control for cloud-assisted Industrial Internet of Things (IIoT). However, existing schemes suffer from the following drawbacks: (1) their computational overhead in data outsourcing and retrieval is exceptionally high; (2) they obtain wrong search results if one or more of the queried keywords are wrongly selected; (3) in most existing ABKS, the untrustworthiness of the cloud server is not taken into account, and the correctness of the search results is not verified; (4) existing verifiable ABKS schemes do not support search results verification without the main data, and verifiers have to first download the search results and then check their correctness. In this paper, we design a verifiable online/offline multi-keyword search (VMKS) scheme providing high-level solutions to the aforementioned problems. We use the healthcare setting as a case study, and we demonstrate how our VMKS can be deployed in cloud-assisted Healthcare IIoT (HealthIIoT). We prove the security of our VMKS in the standard model and under the hardness assumption of the decisional bilinear Diffie-Hellman (DBDH) problem. Empirical results demonstrate that our VMKS speeds up encryption and verification processes by more than 70% and 90%, respectively. Moreover, our scheme reduces the communication overhead in the verification phase by more than 80%.
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Journal of Information Security and Applications
dc.relation.isbasedon	10.1016/j.jisa.2021.103101
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Verifiable online/offline multi-keyword search for cloud-assisted Industrial Internet of Things
dc.type	Journal Article
utslib.citation.volume	65
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2022-12-07T19:46:31Z
pubs.publication-status	Published
pubs.volume	65

Abstract:

Attribute-based encryption (ABE) and attribute-based keyword search (ABKS) facilitate fine-grained access and search control for cloud-assisted Industrial Internet of Things (IIoT). However, existing schemes suffer from the following drawbacks: (1) their computational overhead in data outsourcing and retrieval is exceptionally high; (2) they obtain wrong search results if one or more of the queried keywords are wrongly selected; (3) in most existing ABKS, the untrustworthiness of the cloud server is not taken into account, and the correctness of the search results is not verified; (4) existing verifiable ABKS schemes do not support search results verification without the main data, and verifiers have to first download the search results and then check their correctness. In this paper, we design a verifiable online/offline multi-keyword search (VMKS) scheme providing high-level solutions to the aforementioned problems. We use the healthcare setting as a case study, and we demonstrate how our VMKS can be deployed in cloud-assisted Healthcare IIoT (HealthIIoT). We prove the security of our VMKS in the standard model and under the hardness assumption of the decisional bilinear Diffie-Hellman (DBDH) problem. Empirical results demonstrate that our VMKS speeds up encryption and verification processes by more than 70% and 90%, respectively. Moreover, our scheme reduces the communication overhead in the verification phase by more than 80%.

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http://hdl.handle.net/10453/164208