AI-based Sensor Fingerprinting for Device Identification.

AI-based Sensor Fingerprinting for Device Identification.

Srivignessh Pss

Srivignessh Pss

Tempe, Arizona

Mobile/Wearable sensors have its own unique manufacturing defects. The AI developed learns these calibrations for identification of devices

Artificial Intelligence, Internet of Things

Description

Wearable and Mobile Device Accelerometer has linear calibration measurements. This provides us with two metrics sensitivity and offsets in each of the axes (X, Y, Z) to model. Hence there are 6 metrics for each device. Adaptive Neural Networks is used to learn these parameters to uniquely identify a device.

In the figure, You can see the POC. Three clusters represent (the Z axes) sensitivity and offsets of three devices. Example Devices used: Moto G, Mi4i, and Ipad.

References 1> https://crypto.stanford.edu/gyrophone/sensor_id.pdf 2> http://ieeexplore.ieee.org/document/7522434/

Links

Sensitivity vs Offset for Z axis

Standard index1

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