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AI-based Sensor Fingerprinting for Device Identification.

Srivignessh Pss

Srivignessh Pss

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

Internet of Things, Artificial Intelligence

Groups
Hacker Lab IoT, Student Developers for AI

Overview / Usage

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.
Video Link: http://bcove.me/85s5ga3z
References
1> https://crypto.stanford.edu/gyrophone/sensor_id.pdf
2> http://ieeexplore.ieee.org/document/7522434/

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