Real-world Commercial WiFi and Bluetooth Dataset for RF Fingerprinting

Citation Author(s):
Anu
Jagannath
ANDRO COMPUTATIONAL SOLUTIONS, LLC
Zackary
Kane
ANDRO COMPUTATIONAL SOLUTIONS LLC
Jithin
Jagannath
ANDRO COMPUTATIONAL SOLUTIONS LLC
Submitted by:
Anu Jagannath
Last updated:
Mon, 10/31/2022 - 11:40
DOI:
10.21227/618k-c392
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Abstract 

A real-world radio frequency (RF) fingerprinting dataset for commercial off-the-shelf (COTS) Bluetooth and WiFi emitters under challenging testbed setups is presented in this dataset. The chipsets within the devices (2 laptops and 8 commercial chips) are WiFi-Bluetooth combo transceivers. The emissions are captured with a National Instruments Ettus USRP X300 radio outfitted with a UBX160 daughterboard and a VERT2450 antenna. The receiver is tuned to record a 66.67 MHz bandwidth of the spectrum centered at the 2.414 GHz frequency. This is a first-of-its-kind dataset for fingerprinting WiFi-Bluetooth combo chipsets that are commonly found in today's IoT era. The dataset is split into two for WiFi and Bluetooth -  Day1 and Day2 - each of which is recorded in a different time frame but under the same receiver settings to enable a critical generalization test of the trained deep learning (DL) model. The authors suggest training the DL model with the Day1 dataset with recordings under varied Bluetooth and WiFi signal strengths followed by evaluating the generalization capability of the model with the Day2 dataset which is a challenging and different setup compared to Day1. This evaluation will validate the realistic deployment capability of the trained DL model. The dataset follows the SigMF specifications with certain field extensions to facilitate the fingerprinting application and include additional metadata fields. Each capture is of length 40 Mega Samples (MS) and is associated with a JSON metadata file.

Instructions: 

The dataset contains two separate datasets each for WiFi and Bluetooth collected under different time frames.

  1. Day1BT.tar.gz: Commercial Bluetooth device emissions collected under line-of-sight conditions at varying distances per emitter as indicated in the associated JSON metadata file of each capture during timeframe-1 denoted for ease as Day-1. The transmitter-receiver separation ranges from 0.5 m to 3.0 m in steps of 0.5 m.
  2. Day2BT.tar.gz: Commercial Bluetooth device emissions collected under line-of-sight conditions at varying distances per emitter as indicated in the associated JSON metadata file of each capture during timeframe-2 denoted for ease as Day-2. The transmitter-receiver separation ranges from 0.5 m to 3.0 m in steps of 0.5 m.
  3. Day1WIFI.tar.gz: Commercial WiFi device emissions collected under line-of-sight conditions at varying transmission power per emitter as indicated in the associated JSON metadata file of each capture during timeframe-1 denoted for ease as Day-1. 
  4. Day2WIFI.tar.gz: Commercial WiFi device emissions collected under line-of-sight conditions at varying transmission power per emitter as indicated in the associated JSON metadata file of each capture during timeframe-2 denoted for ease as Day-2.

Each dataset contains a binary capture file (.dat) and an associated JSON metadata file (.meta.json). The capture file contains complex64 inphase-quadrature (IQ) samples and the JSON contains the metadata which characterizes the data capture environment.

How to cite this dataset? Please cite the original paper.

Bibtex:

@inproceedings{AJagannath22GLOBECOM,author = "A. Jagannath, Z. Kane, J. Jagannath",title = "{RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth}",booktitle = "Proc. of IEEE Global Communications Conference (GLOBECOM)",address = "Rio de Janeiro, Brazil",month = "December",year = "2022"}

Plain text:

A. Jagannath, Z. Kane, J. Jagannath, “RF Fingerprinting Needs Attention: Multi-task Approach for Real-World WiFi and Bluetooth” in Proc. of IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, December 2022.