BreathPrint: Breathing acoustics-based user authentication

We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are suff...

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Main Authors: CHAUHAN, Jagmohan, HU, Yining, SEREVIRATNE, Suranga, MISRA, Archan, SEREVIRATNE, Aruna, LEE, Youngki
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Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/sis_research/3792
https://ink.library.smu.edu.sg/context/sis_research/article/4794/viewcontent/mobisys17_paper18_av.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-47942020-06-09T02:05:38Z BreathPrint: Breathing acoustics-based user authentication CHAUHAN, Jagmohan HU, Yining SEREVIRATNE, Suranga MISRA, Archan SEREVIRATNE, Aruna LEE, Youngki We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users can be authenticated reliably with an accuracy of over 94% for all the three breathing gestures in intra-sessions and deep breathing gesture provides the best overall balance between true positives (successful authentication) and false positives (resiliency to directed impersonation and replay attacks). Moreover, we show that this breathing sound based biometric is also robust to some typical changes in both physiological and environmental context, and that it can be applied on multiple smartphone platforms. Early results suggest that breathing based biometrics show promise as either to be used as a secondary authentication modality in a multimodal biometric authentication system or as a user disambiguation technique for some daily lifestyle scenarios. 2017-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3792 info:doi/10.1145/3081333.3081355 https://ink.library.smu.edu.sg/context/sis_research/article/4794/viewcontent/mobisys17_paper18_av.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 Authentication Breathing gestures Security Usability Databases and Information Systems Information Security Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Authentication
Breathing gestures
Security
Usability
Databases and Information Systems
Information Security
Software Engineering
spellingShingle Authentication
Breathing gestures
Security
Usability
Databases and Information Systems
Information Security
Software Engineering
CHAUHAN, Jagmohan
HU, Yining
SEREVIRATNE, Suranga
MISRA, Archan
SEREVIRATNE, Aruna
LEE, Youngki
BreathPrint: Breathing acoustics-based user authentication
description We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users can be authenticated reliably with an accuracy of over 94% for all the three breathing gestures in intra-sessions and deep breathing gesture provides the best overall balance between true positives (successful authentication) and false positives (resiliency to directed impersonation and replay attacks). Moreover, we show that this breathing sound based biometric is also robust to some typical changes in both physiological and environmental context, and that it can be applied on multiple smartphone platforms. Early results suggest that breathing based biometrics show promise as either to be used as a secondary authentication modality in a multimodal biometric authentication system or as a user disambiguation technique for some daily lifestyle scenarios.
format text
author CHAUHAN, Jagmohan
HU, Yining
SEREVIRATNE, Suranga
MISRA, Archan
SEREVIRATNE, Aruna
LEE, Youngki
author_facet CHAUHAN, Jagmohan
HU, Yining
SEREVIRATNE, Suranga
MISRA, Archan
SEREVIRATNE, Aruna
LEE, Youngki
author_sort CHAUHAN, Jagmohan
title BreathPrint: Breathing acoustics-based user authentication
title_short BreathPrint: Breathing acoustics-based user authentication
title_full BreathPrint: Breathing acoustics-based user authentication
title_fullStr BreathPrint: Breathing acoustics-based user authentication
title_full_unstemmed BreathPrint: Breathing acoustics-based user authentication
title_sort breathprint: breathing acoustics-based user authentication
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/sis_research/3792
https://ink.library.smu.edu.sg/context/sis_research/article/4794/viewcontent/mobisys17_paper18_av.pdf
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