Title
PrivGait: An Energy Harvesting-based Privacy-Preserving User Identification System by Gait Analysis
Author
Xu, Weitao (City University of Hong Kong)
Xue, Wanli (Cybersecurity Cooperative Research Centre)
Lin, Qi (University of New South Wales)
Lan, G. (TU Delft Embedded and Networked Systems)
Feng, Xingyu (Shenzhen University)
Wei, Bo (University of Northumbria)
Luo, Chengwen (Shenzhen University)
Li, Wei (University of Sydney)
Zomaya, Albert Y. (University of Sydney)
Date
2022
Abstract
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.
Subject
Energy harvesting
Feature extraction
Gait recognition
IoT security
Privacy
privacy preserving.
Sensors
smart space
Smart spaces
Wearable computers
To reference this document use:
http://resolver.tudelft.nl/uuid:154ad321-b6bd-4839-8ed0-eba38091428c
DOI
https://doi.org/10.1109/JIOT.2021.3089618
Embargo date
2023-07-01
ISSN
2327-4662
Source
IEEE Internet of Things Journal, 9 (22), 22048-22060
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2022 Weitao Xu, Wanli Xue, Qi Lin, G. Lan, Xingyu Feng, Bo Wei, Chengwen Luo, Wei Li, Albert Y. Zomaya