Leveraging Sensor Fingerprinting for Mobile Device Authentication
Device fingerprinting is a technique for identification and recognition of clients and widely used in practice for Web tracking and fraud prevention. While common systems depend on software attributes, sensor based fingerprinting relies on hardware imperfections and thus opens up new possibilities for device authentication. Recent work focusses on accelerometers as easily accessible sensors of modern mobile devices. However, it has remained unclear if device recognition via sensor based fingerprinting is feasible under real world conditions. In this paper, we analyze the effectiveness of a specialized feature set for sensor based device fingerprinting and compare the results to feature less fingerprinting techniques based on raw measurements. Furthermore, we evaluate other sensor types like gravity and magnetic field sensors as well as combinations of different sensors concerning their suitability for the purpose of device authentication. We demonstrate that combinations of different sensors yield precise device fingerprints when evaluating the approach on a real world data set consisting of empirical measurement results obtained from almost 5,000 devices.
DIMVA