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Lookup NU author(s): Dr Bo WeiORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by Institute of Electrical and Electronics Engineers Inc., 2022.
For re-use rights please refer to the publisher's terms and conditions.
© 2014 IEEE.Smart space has emerged as a new paradigm that combines sensing, communication, and artificial intelligence technologies to offer various customized services. A fundamental requirement of these services is person identification. Although a variety of person-identification approaches has been proposed, they suffer from several limitations in practical applications, such as low energy efficiency, accuracy degradation, and privacy issue. This article proposes an energy-harvesting-based privacy-preserving gait recognition scheme for smart space, which is named PrivGait. In PrivGait, we extract discriminative features from 1-D gait signal and design an attention-based long short-term memory (LSTM) network to classify different people. Moreover, we leverage a novel Bloom filter-based privacy-preserving technique to address the privacy leakage problem. To demonstrate the feasibility of PrivGait, we design a proof-of-concept prototype using off-the-shelf energy-harvesting hardware. Extensive evaluation results show that the proposed scheme outperforms state of the art by 6%-10% and incurs low system cost while preserving user's privacy.
Author(s): Xu W, Xue W, Lin Q, Lan G, Feng X, Wei B, Luo C, Li W, Zomaya AY
Publication type: Article
Publication status: Published
Journal: IEEE Internet of Things Journal
Year: 2022
Volume: 9
Issue: 22
Pages: 22048-22060
Print publication date: 15/11/2022
Online publication date: 15/06/2021
Acceptance date: 07/06/2021
Date deposited: 29/06/2023
ISSN (electronic): 2327-4662
Publisher: Institute of Electrical and Electronics Engineers Inc.
URL: https://doi.org/10.1109/JIOT.2021.3089618
DOI: 10.1109/JIOT.2021.3089618
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