Efficient Encrypted Range Query on Cloud Platforms

Yu, P; Ni, W; Liu, RP; Zhang, Z; Zhang, H; Wen, Q

Efficient Encrypted Range Query on Cloud Platforms

Yu, P Ni, W

Liu, RP Zhang, Z Zhang, H Wen, Q

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Publisher:: Association for Computing Machinery (ACM)
Publication Type:: Journal Article
Citation:: ACM Transactions on Cyber-Physical Systems, 2022, 6, (3), pp. 1-23
Issue Date:: 2022-09-07

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Field	Value	Language
dc.contributor.author	Yu, P
dc.contributor.author	Ni, W https://orcid.org/0000-0002-4933-594X
dc.contributor.author	Liu, RP
dc.contributor.author	Zhang, Z
dc.contributor.author	Zhang, H
dc.contributor.author	Wen, Q
dc.date.accessioned	2023-04-20T03:18:36Z
dc.date.available	2023-04-20T03:18:36Z
dc.date.issued	2022-09-07
dc.identifier.citation	ACM Transactions on Cyber-Physical Systems, 2022, 6, (3), pp. 1-23
dc.identifier.issn	2378-962X
dc.identifier.issn	2378-9638
dc.identifier.uri	http://hdl.handle.net/10453/170017
dc.description.abstract	In the Internet of Things (IoT) era, various IoT devices are equipped with sensing capabilities and employed to support clinical applications. The massive electronic health records (EHRs) are expected to be stored in the cloud, where the data are usually encrypted, and the encrypted data can be used for disease diagnosis. There exist some numeric health indicators, such as blood pressure and heart rate. These numeric indicators can be classified into multiple ranges, and each range may represent an indication of normality or abnormity. Once receiving encrypted IoT data, the CS maps it to one of the ranges, achieving timely monitoring and diagnosis of health indicators. This article presents a new approach to identify the range that an encrypted numeric value corresponds to without exposing the explicit value. We establish the sufficient and necessary condition to convert a range query to matchings of encrypted binary sequences with the minimum number of matching operations. We further apply the minimization of range queries to design and implement a secure range query system, where numeric health indicators encrypted independently by multiple IoT devices can be cohesively stored and efficiently queried by using Lagrange polynomial interpolation. Comprehensive performance studies show that the proposed approach can protect both the health records and range query against untrusted cloud platforms and requires less computational and communication cost than existing techniques.
dc.language	en
dc.publisher	Association for Computing Machinery (ACM)
dc.relation.ispartof	ACM Transactions on Cyber-Physical Systems
dc.relation.isbasedon	10.1145/3548657
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Efficient Encrypted Range Query on Cloud Platforms
dc.type	Journal Article
utslib.citation.volume	6
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	2023-04-20T03:18:34Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	6
utslib.citation.issue	3

Abstract:

In the Internet of Things (IoT) era, various IoT devices are equipped with sensing capabilities and employed to support clinical applications. The massive electronic health records (EHRs) are expected to be stored in the cloud, where the data are usually encrypted, and the encrypted data can be used for disease diagnosis. There exist some numeric health indicators, such as blood pressure and heart rate. These numeric indicators can be classified into multiple ranges, and each range may represent an indication of normality or abnormity. Once receiving encrypted IoT data, the CS maps it to one of the ranges, achieving timely monitoring and diagnosis of health indicators. This article presents a new approach to identify the range that an encrypted numeric value corresponds to without exposing the explicit value. We establish the sufficient and necessary condition to convert a range query to matchings of encrypted binary sequences with the minimum number of matching operations. We further apply the minimization of range queries to design and implement a secure range query system, where numeric health indicators encrypted independently by multiple IoT devices can be cohesively stored and efficiently queried by using Lagrange polynomial interpolation. Comprehensive performance studies show that the proposed approach can protect both the health records and range query against untrusted cloud platforms and requires less computational and communication cost than existing techniques.

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http://hdl.handle.net/10453/170017