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Gyrophone: Recognizing Speech from Gyroscope Signals

Friday, July 25, 2014 - 5:15pm
Authors: 

Yan Michalevsky and Dan Boneh, Stanford University; Gabi Nakibly, National Research & Simulation Center, Rafael Ltd.

Abstract: 

We show that the MEMS gyroscopes found on modern smart phones are sufficiently sensitive to measure acoustic signals in the vicinity of the phone. The resulting signals contain only very low-frequency information (<200Hz). Nevertheless we show, using signal processing and machine learning, that this information is sufficient to identify speaker information and even parse speech. Since iOS and Android require no special permissions to access the gyro, our results show that apps and active web content that cannot access the microphone can nevertheless eavesdrop on speech in the vicinity of the phone.

Yan Michalevsky, Stanford University

Dan Boneh, Stanford University

Gabi Nakibly, National Research & Simulation Center, Rafael Ltd.

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BibTeX
@inproceedings {184479,
author = {Yan Michalevsky and Dan Boneh and Gabi Nakibly},
title = {Gyrophone: Recognizing Speech from Gyroscope Signals},
booktitle = {23rd USENIX Security Symposium (USENIX Security 14)},
year = {2014},
isbn = {978-1-931971-15-7},
address = {San Diego, CA},
pages = {1053--1067},
url = {https://www.usenix.org/conference/usenixsecurity14/technical-sessions/presentation/michalevsky},
publisher = {USENIX Association},
month = aug,
}
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