Extension of physical activity recognition with 3D CNN using encrypted multiple sensory data to federated learning based on multi-key homomorphic encryption-Reference-Cited by-同舟云学术

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Extension of physical activity recognition with 3D CNN using encrypted multiple sensory data to federated learning based on multi-key homomorphic encryption

Published:2024-01 Issue: Volume:243 Page:107854
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Pham Chi-Hieu,Huynh-The Thien,Sedgh-Gooya Ehsan,El-Bouz Marwa,Alfalou Ayman

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference72 articles.

1. Recent advances in homomorphic encryption: a possible future for signal processing in the encrypted domain;Aguilar-Melchor;IEEE Signal Process. Mag.,2013

2. Comparative study on classifying human activities with miniature inertial and magnetic sensors;Altun;Pattern Recognit.,2010

3. A public domain dataset for human activity recognition using smartphones;Anguita,2013

4. Privacy-preserving deep learning via additively homomorphic encryption;Aono;IEEE Trans. Inf. Forensics Secur.,2017

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