Wireless Physical Layer Identification of Bluetooth Smart Signals

Exploiting the unique properties of physical RF signals to identify and classify authorized devices. Caused by numerous production variations, these properties create a Physical Unclonable Function (PUF) which is very hard to forge and promises an important technique in Wireless Security (e.g. IoT).

Dialog Semiconductor BV

Dialog Semiconductor BV is the Dutch subsidiary of Dialog. Dialog Semiconductor BV is focusing on ICs for short range wireless standards. It is the number one provider of System-on-Chip devices in wireless audio, Bluetooth Smart solutions, 802.15.4 and Digital Cordless.

Bluetooth Smart

Dialog is offering best-in-class fully integrated BLE solutions that are being used in many applications such as the wearable mi-band of Xiaomi, thermostats produced by NEST (a google company) etc.

A wide range of Bluetooth Smart products has been adopted by numerous leading manufacturers of wearables, integrating a Bluetooth Smart radio, ARM Cortex-M0 and/or M33 application processor and intelligent power management. It more than doubles the battery life of application-enabled smartphone accessories, wearable devices or computer peripheral in comparison to competing solutions.

Assignment

Getting insight in using commercial Bluetooth Smart devices for extraction of this RF-DNA. Theoretical modeling of different feature-extracting and classification algorithms. Implementing algorithms on Dialog Bluetooth Smart chips and performing measurements (False Acceptance/Rejection, SNR, multipath, interference).

Requirements

Statistical signal processing, digital signal processing, matlab, C, C++, embedded programming

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Last modified: 2022-10-04