EarSpy: Eavesdropping Using Motion Sensors
Ahmed Tanvir Mahdad et al. (PDF via Bruce Schneier):
We explore recent trends in smartphone manufacturers that include extra/powerful speakers in place of small ear speakers, and demonstrate the feasibility of using motion sensors to capture such tiny speech vibrations. We investigate the impacts of these new ear speakers on built-in motion sensors and examine the potential to elicit private speech information from the minute vibrations. Our designed system EarSpy can successfully detect word regions, time, and frequency domain features and generate a spectrogram for each word region. We train and test the extracted data using classical machine learning algorithms and convolutional neural networks. We found up to 98.66% accuracy in gender detection, 92.6% detection in speaker detection, and 56.42% detection in digit detection (which is 5X more significant than the random selection (10%)).
Previously:
- Typewriter Keylogger
- Stealing Sensitive Browser Data With the W3C Ambient Light Sensor API
- Secret Audio and Key Recording
- Ads Use Inaudible Sound to Link Your Devices
