Please use this identifier to cite or link to this item:
Title: Achieve privacy-preserving priority classification on patient health data in remote eHealthcare system
Authors: Wang, Guoming
Lu, Rongxing
Guan, Yong Liang
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Remote eHealthcare
Issue Date: 2019
Source: Wang, G., Lu, R., & Guan, Y. L. (2019). Achieve privacy-preserving priority classification on patient health data in remote eHealthcare system. IEEE Access, 7, 33565-33576. doi:10.1109/ACCESS.2019.2891775
Series/Report no.: IEEE Access
Abstract: The wireless body area network (WBAN) has attracted considerable attention and becomes a promising approach to provide a 24-h on-the-go healthcare service for users. However, it still faces many challenges on the privacy of users' sensitive personal information and the confidentiality of healthcare center's disease models. For this reason, many privacy-preserving schemes have been proposed in recent years. However, the efficiency and accuracy of those privacy-preserving schemes become a big issue to be solved. In this paper, we propose an efficient and privacy-preserving priority classification scheme, named PPC, for classifying patients' encrypted data at the WBAN-gateway in a remote eHealthcare system. Specifically, to reduce the system latency, we design a non-interactive privacy-preserving priority classification algorithm, which allows the WBAN-gateway to conduct the privacy-preserving priority classification for the received users' medical packets by itself and to relay these packets according to their priorities (criticalities). A detailed security analysis shows that the PPC scheme can achieve the priority classification and packets relay without disclosing the privacy of the users' personal information and the confidentiality of the healthcare center's disease models. In addition, the extensive experiments with an android app and two java server programs demonstrate its efficiency in terms of computational costs and communication overheads.
DOI: 10.1109/ACCESS.2019.2891775
Rights: © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

Citations 20

Updated on Sep 3, 2020

Citations 20

Updated on Mar 2, 2021

Page view(s)

Updated on Jun 14, 2021

Download(s) 50

Updated on Jun 14, 2021

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.