Privacy-Aware Fuzzy Range Query Processing Over Distributed Edge Devices

Yinglong Li; Weiru Liu; Yihua Zhu; Hong Chen; Hongbing Cheng; Tieming Chen; Ping Hu; Ruohong Huan

doi:10.1109/TFUZZ.2021.3059952

Privacy-Aware Fuzzy Range Query Processing Over Distributed Edge Devices

Yinglong Li, Weiru Liu, Yihua Zhu, Hong Chen, Hongbing Cheng, Tieming Chen, Ping Hu, Ruohong Huan

Department of Engineering Mathematics

Research output: Contribution to journal › Article (Academic Journal) › peer-review

7 Citations (Scopus)

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Abstract

Range query processing is a common edge computing and service in the Internet of Things, which can extract user-interest information from distributed edge devices. How to design lightweight privacy-preserving range query processing methods remains a challenging task. Existing secure range query approaches suffer from both high communication cost and long response time, which makes them unsuitable for edge computing over resource-constrained edge devices. In this paper, we propose two privacy-aware fuzzy query processing schemes based on fuzzy theory. Linguistic range variables, fuzzy overlap information and its recovery mechanism are introduced respectively. In addition, two distributed privacy-aware fuzzy range query processing algorithms are devised. Our approaches not only serve for privacy protection, but also aim to provide other optimal performances in terms of reliability, energy efficiency, and real-time response. Theoretical analysis and experimental evaluations based on real-world data sets validated our motivation.

Original language	English
Journal	IEEE Transactions on Fuzzy Systems
DOIs	https://doi.org/10.1109/TFUZZ.2021.3059952
Publication status	Published - 17 Feb 2021

Bibliographical note

Funding Information:
This work was supported by the National Natural Science Foundation of China (Grant no. 11402205), the Fundamental Research Funds for the Central Universities of China (Grant no. 310201401JCQ01015), the Innovation Funds of CALT for Unversities of China (Grant no. CALT201508) and the 111 Project of China (Grant no.B07050). Guo gratefully thank Professor Dong Wang for their helpful suggestions.

Publisher Copyright:
IEEE

Keywords

range query
fuzzy sets
edge computing
Internet of Things
privacy protection

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at https://doi.org/10.1109/TFUZZ.2021.3059952 . Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 1.04 MB

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abstract = "Range query processing is a common edge computing and service in the Internet of Things, which can extract user-interest information from distributed edge devices. How to design lightweight privacy-preserving range query processing methods remains a challenging task. Existing secure range query approaches suffer from both high communication cost and long response time, which makes them unsuitable for edge computing over resource-constrained edge devices. In this paper, we propose two privacy-aware fuzzy query processing schemes based on fuzzy theory. Linguistic range variables, fuzzy overlap information and its recovery mechanism are introduced respectively. In addition, two distributed privacy-aware fuzzy range query processing algorithms are devised. Our approaches not only serve for privacy protection, but also aim to provide other optimal performances in terms of reliability, energy efficiency, and real-time response. Theoretical analysis and experimental evaluations based on real-world data sets validated our motivation.",

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author = "Yinglong Li and Weiru Liu and Yihua Zhu and Hong Chen and Hongbing Cheng and Tieming Chen and Ping Hu and Ruohong Huan",

note = "Funding Information: This work was supported by the National Natural Science Foundation of China (Grant no. 11402205), the Fundamental Research Funds for the Central Universities of China (Grant no. 310201401JCQ01015), the Innovation Funds of CALT for Unversities of China (Grant no. CALT201508) and the 111 Project of China (Grant no.B07050). Guo gratefully thank Professor Dong Wang for their helpful suggestions. Publisher Copyright: IEEE",

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AU - Li, Yinglong

AU - Liu, Weiru

AU - Zhu, Yihua

AU - Chen, Hong

AU - Cheng, Hongbing

AU - Chen, Tieming

AU - Hu, Ping

AU - Huan, Ruohong

N1 - Funding Information: This work was supported by the National Natural Science Foundation of China (Grant no. 11402205), the Fundamental Research Funds for the Central Universities of China (Grant no. 310201401JCQ01015), the Innovation Funds of CALT for Unversities of China (Grant no. CALT201508) and the 111 Project of China (Grant no.B07050). Guo gratefully thank Professor Dong Wang for their helpful suggestions. Publisher Copyright: IEEE

PY - 2021/2/17

Y1 - 2021/2/17

N2 - Range query processing is a common edge computing and service in the Internet of Things, which can extract user-interest information from distributed edge devices. How to design lightweight privacy-preserving range query processing methods remains a challenging task. Existing secure range query approaches suffer from both high communication cost and long response time, which makes them unsuitable for edge computing over resource-constrained edge devices. In this paper, we propose two privacy-aware fuzzy query processing schemes based on fuzzy theory. Linguistic range variables, fuzzy overlap information and its recovery mechanism are introduced respectively. In addition, two distributed privacy-aware fuzzy range query processing algorithms are devised. Our approaches not only serve for privacy protection, but also aim to provide other optimal performances in terms of reliability, energy efficiency, and real-time response. Theoretical analysis and experimental evaluations based on real-world data sets validated our motivation.

AB - Range query processing is a common edge computing and service in the Internet of Things, which can extract user-interest information from distributed edge devices. How to design lightweight privacy-preserving range query processing methods remains a challenging task. Existing secure range query approaches suffer from both high communication cost and long response time, which makes them unsuitable for edge computing over resource-constrained edge devices. In this paper, we propose two privacy-aware fuzzy query processing schemes based on fuzzy theory. Linguistic range variables, fuzzy overlap information and its recovery mechanism are introduced respectively. In addition, two distributed privacy-aware fuzzy range query processing algorithms are devised. Our approaches not only serve for privacy protection, but also aim to provide other optimal performances in terms of reliability, energy efficiency, and real-time response. Theoretical analysis and experimental evaluations based on real-world data sets validated our motivation.

KW - range query

KW - fuzzy sets

KW - edge computing

KW - Internet of Things

KW - privacy protection

U2 - 10.1109/TFUZZ.2021.3059952

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M3 - Article (Academic Journal)

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JO - IEEE Transactions on Fuzzy Systems

JF - IEEE Transactions on Fuzzy Systems

ER -

Privacy-Aware Fuzzy Range Query Processing Over Distributed Edge Devices

Abstract

Bibliographical note

Keywords

UN SDGs

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