Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
6-2017
Abstract
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.
Keywords
Authentication, Breathing gestures, Security, Usability
Discipline
Databases and Information Systems | Information Security | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
MobiSys '17: Proceedings of the 15th International Conference on Mobile Systems, Applications, and Services: June 19-23, Niagara Falls
First Page
278
Last Page
291
ISBN
9781450349284
Identifier
10.1145/3081333.3081355
Publisher
ACM
City or Country
New York
Citation
CHAUHAN, Jagmohan; HU, Yining; SEREVIRATNE, Suranga; MISRA, Archan; SEREVIRATNE, Aruna; and LEE, Youngki.
BreathPrint: Breathing acoustics-based user authentication. (2017). MobiSys '17: Proceedings of the 15th International Conference on Mobile Systems, Applications, and Services: June 19-23, Niagara Falls. 278-291.
Available at: https://ink.library.smu.edu.sg/sis_research/3792
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3081333.3081355
Included in
Databases and Information Systems Commons, Information Security Commons, Software Engineering Commons