Optimal deployment of face recognition solutions in a heterogeneous IoT platform for secure elderly care applications
Egileak: Ignacio Arganda-Carreras
Data: 10.09.2021
Procedia Computer Science
Abstract
Face recognition provides a desirable solution for authentication and surveillance in Internet of Things platforms for elderly care. However, its inclusion is challenging because of the possibly reduced interaction capabilities of users, the high variety of interaction devices, and the need of managing biometric data securely. Our approach relies on lightweight deep neural networks for secure recognition and to guide users during interaction. An automated procedure selects the appropriate inference engine, model configurations, and batch size, based on edge device characteristics. Biometric data is homomorphically encrypted to preserve privacy. An evaluation with respect to state-of-the-art alternatives shows its potential.
BIB_text
title = {Optimal deployment of face recognition solutions in a heterogeneous IoT platform for secure elderly care applications},
journal = {Procedia Computer Science},
pages = {3204-3213},
volume = {192},
keywds = {
Face Recognition, Deep Neural Networks, Internet of Things, Elderly Care
}
abstract = {
Face recognition provides a desirable solution for authentication and surveillance in Internet of Things platforms for elderly care. However, its inclusion is challenging because of the possibly reduced interaction capabilities of users, the high variety of interaction devices, and the need of managing biometric data securely. Our approach relies on lightweight deep neural networks for secure recognition and to guide users during interaction. An automated procedure selects the appropriate inference engine, model configurations, and batch size, based on edge device characteristics. Biometric data is homomorphically encrypted to preserve privacy. An evaluation with respect to state-of-the-art alternatives shows its potential.
}
doi = {10.1016/j.procs.2021.09.093},
date = {2021-09-10},
}
