PrivGait

PrivGait: An Energy Harvesting-based Privacy-Preserving User Identification System by Gait Analysis

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 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)

2022

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.

Energy harvesting
Feature extraction
Gait recognition
IoT security
Privacy
privacy preserving.
Sensors
smart space
Smart spaces
Wearable computers

http://resolver.tudelft.nl/uuid:154ad321-b6bd-4839-8ed0-eba38091428c

https://doi.org/10.1109/JIOT.2021.3089618

2023-07-01

2327-4662

IEEE Internet of Things Journal, 9 (22), 22048-22060

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.

Institutional Repository

journal article

© 2022 Weitao Xu, Wanli Xue, Qi Lin, G. Lan, Xingyu Feng, Bo Wei, Chengwen Luo, Wei Li, Albert Y. Zomaya