Yet Another Security Flaw Possible In Your Smartphone

Researchers Find a Way to Snoop on You through Your Phone’s Vibration Motor

Devin Coldewey | June 7, 2016

Cover up your webcam, disable microphone access and put on your tinfoil hat — but it won’t make any difference, because the Illuminati can get at you through your phone’s vibration motor now. Well, kind of, anyway. Your best defense? Talk in a high voice.
The “VibraPhone” research comes from Romit Roy Choudhury and Nirupam Roy, associate professor and PhD candidate, respectively, at the Electrical and Computer Engineering school of the University of Illinois at Ubana-Champaign.
It’s a surprisingly simple idea, really: A vibration motor is really like a tiny speaker. And every speaker can be a microphone. Think about it.

Typical smartphone with vibrator motor. "HTC One Display Assembly Replacement."  Vibrator Motor Removal. Source: https://www.ifixit.com/Guide/HTC+One+Display+Assembly+Replacement/19277

<more at http://techcrunch.com/2016/06/06/researchers-find-a-way-to-snoop-on-you-through-your-phones-vibration-motor/; related articles and links: http://synrg.csl.illinois.edu/vibraphone/ (VibraPhone: Listening through a Vibration Motor. [webpage not yet formally published]) and http://synrg.csl.illinois.edu/vibraphone/paperdocs/VibraPhone_nirupam.pdf (Listening through a Vibration Motor. Nirupam Roy and Romit Roy Choudhury. To be presented at MobiSys’16, June 25 - 30, 2016, Singapore. DOI: http://dx.doi.org/10.1145/2906388.2906415. [Abstract: This paper demonstrates the feasibility of using the vibration motor in mobile devices as a sound sensor, almost like
a microphone. We show that the vibrating mass inside the motor – designed to oscillate to changing magnetic fields – also responds to air vibrations from nearby sounds. With
appropriate processing, the responses become intelligible, to the extent that humans can understand the vibra-motor recorded words with greater than 80% average accuracy.
Even off-the-shelf speech recognition softwares are able to decode at 60% accuracy, without any training or machine learning. While these findings are not fundamentally surprising (given that any vibrating object should respond to air vibrations), the fidelity to which this is possible has been somewhat unexpected. We present our overall techniques
and results through a system called VibraPhone, and discuss implications to both sensing and security.])>