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

Xu, Weitao and Lin, Qi and Xue, Wanli and Lan, Guohao and Feng, Xingyu and Wei, Bo and Luo, Chengwen and Li, Wei and Zomaya, Albert (2022) PrivGait:An Energy Harvesting-based Privacy-Preserving User Identification System by Gait Analysis. IEEE Internet of Things Journal, 9 (22). pp. 22048-22060. ISSN 2327-4662

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Smart space has emerged as a new paradigm that combines sensing, communication, and artificial intelligence technologies to offer various customised services. A fundamental requirement of these services is person identification. Although a variety of person identification approaches have been proposed, they suffer from several limitations in practical applications such as low energy efficiency, accuracy degradation, and privacy issue. This paper proposes an energy harvesting based privacy-preserving gait recognition scheme for smart space which is named . In , we extract discriminative features from one-dimensional 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 , 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.

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Journal Article
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IEEE Internet of Things Journal
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14 Jun 2022 15:35
Last Modified:
22 Nov 2022 11:33