Date of Award


Document Type

Open Access Thesis


Computer Science and Engineering

First Advisor

Srihari Nelakuditi


This paper submits a hypothesis that smartphone accelerometers possess unique fingerprints. We believe that the fingerprints arise from hardware imperfections during the sensor manufacturing process, causing every sensor chip to respond differently to the same motion stimulus. The differences in responses are subtle enough that they do not affect most of the higher level functions computed on them. Nonetheless, upon close inspection, these fingerprints emerge with consistency, and can even be somewhat independent of the stimulus that generates them. Measurements and classification on 80 standalone accelerometer chips, 25 Android phones, and 2 tablets, show precision and recall upward of 96%, along with good robustness to real-world conditions. Unsurprisingly, such sensor fingerprints invite new threats in smartphone applications. A crowd-sourcing app running in the cloud could segregate sensor data for each device, making it easy to track a user over space and time. This paper makes the case that such attacks are almost trivial to launch, while simple solutions may not be adequate to counteract them.