Presenter: David Gary
Authors: David Gary, Erick Gutierrez, Ren Quinn
Faculty Advisor: Ren Quinn
Institution: Dixie State University
Three-axis accelerometers, gyroscopes, and magnetometers are a necessary component for modern mobile devices, despite the fact that their data is not protected in the same way recordings from a microphone or camera would be. Studies have shown that this data can be exploited to reveal movement patterns and even matched to previously identified sound wave data for hotword detection. In this work, we attempt to expand what can be produced by using transform methods to extract full sound wave replications without previous identification or machine learning classification systems. Since there are few protections on accelerometer data in place, this study displays a severe vulnerability modern devices have to a new type of side-channel attack via the accelerometer.