Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks

Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks

Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor...

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Main Authors: CHAUHAN, Jagmohan, SENEVIRATNE, Suranga, HU, Yining, MISRA, Archan, SENEVIRATNE, Aruna, LEE, Youngki
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
Subjects:
Digital Communications and Networking
OS and Networks
Online Access:https://ink.library.smu.edu.sg/sis_research/4054
https://ink.library.smu.edu.sg/context/sis_research/article/5057/viewcontent/08364655__1_.pdf
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Institution: Singapore Management University
Language: English
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spelling sg-smu-ink.sis_research-50572018-06-29T06:19:15Z Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks CHAUHAN, Jagmohan SENEVIRATNE, Suranga HU, Yining MISRA, Archan SENEVIRATNE, Aruna LEE, Youngki Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor smart homes. However, the feasibility and performance ofthese inferences on resource-constrained devices remain largelyunexplored. The authors compare traditional machine-learningmodels with deep-learning RNN models for an end-to-endauthentication system based on breathing acoustics. 2018-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4054 info:doi/10.1109/MC.2018.2381119 https://ink.library.smu.edu.sg/context/sis_research/article/5057/viewcontent/08364655__1_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Digital Communications and Networking OS and Networks
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Digital Communications and Networking
OS and Networks
spellingShingle Digital Communications and Networking
OS and Networks
CHAUHAN, Jagmohan
SENEVIRATNE, Suranga
HU, Yining
MISRA, Archan
SENEVIRATNE, Aruna
LEE, Youngki
Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
description Recurrent neural networks (RNNs) have shown promising resultsin audio and speech-processing applications. The increasingpopularity of Internet of Things (IoT) devices makes a strongcase for implementing RNN-based inferences for applicationssuch as acoustics-based authentication and voice commandsfor smart homes. However, the feasibility and performance ofthese inferences on resource-constrained devices remain largelyunexplored. The authors compare traditional machine-learningmodels with deep-learning RNN models for an end-to-endauthentication system based on breathing acoustics.
format text
author CHAUHAN, Jagmohan
SENEVIRATNE, Suranga
HU, Yining
MISRA, Archan
SENEVIRATNE, Aruna
LEE, Youngki
author_facet CHAUHAN, Jagmohan
SENEVIRATNE, Suranga
HU, Yining
MISRA, Archan
SENEVIRATNE, Aruna
LEE, Youngki
author_sort CHAUHAN, Jagmohan
title Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
title_short Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
title_full Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
title_fullStr Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
title_full_unstemmed Breathing-based authentication on resource-constrained IoT devices using recurrent neural networks
title_sort breathing-based authentication on resource-constrained iot devices using recurrent neural networks
publisher Institutional Knowledge at Singapore Management University
publishDate 2018
url https://ink.library.smu.edu.sg/sis_research/4054
https://ink.library.smu.edu.sg/context/sis_research/article/5057/viewcontent/08364655__1_.pdf
_version_ 1770574205078732800

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