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license: gpl-3.0 |
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--- |
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# DeepCSIv2 |
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This is the implementation of the INFOCOM 25 Workshop's (DeepWireless 25) paper-- DeepCSIv2:[Radio Fingerprinting of Wi-Fi Devices Through |
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MIMO Compressed Channel Feedback](https://ieeexplore.ieee.org/abstract/document/11152893) |
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### We present DeepCSIv2, a data-driven radio fingerprinting (RFP) algorithm to characterize Wi-Fi devices acting as stations (STAs) at the physical layer. DeepCSIv2 is based on a neural network architecture that automatically extracts the STA’s radio fingerprint from the feedback captured over the air and identifies the device. |
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If you find the project useful and you use this code, please cite our paper: |
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``` |
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@inproceedings{meneghello2025radio, |
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title={Radio Fingerprinting of Wi-Fi Devices Through MIMO Compressed Channel Feedback}, |
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author={Meneghello, Francesca and Haque, Khandaker Foysal and Restuccia, Francesco}, |
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booktitle={IEEE INFOCOM 2025-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)}, |
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pages={1--6}, |
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year={2025}, |
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organization={IEEE} |
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} |
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``` |
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<br/> |
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<br/> |
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### Please [download the dataset](https://huggingface.co/datasets/foysalhaque/DeepCSIv2/tree/main) and keep in the ```DeepCSIv2/input_files``` directory. You can directly download the Vmatrices or download the raw traces and extract the Vmatrices. The extraction procedure is also provided. |
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### Extract the beamforming feedback with [Wi-BFI Tool](https://github.com/kfoysalhaque/Wi-BFI) |
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```bash |
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python main_extract_batch.py '<trace_dir>' '<standard>' '<MIMO>' '<Antenna-config>' '<BW>' '<packets to process>' '<vmatrices_dir>' '<bfa_dir>' |
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``` |
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Example: python main_extract_batch.py /data/pcap_traces AX MU 4x2 80 5000 /data/output/vmatrices /data/output/bfa |
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#### For any question or query, please contact [Foysal Haque](https://kfoysalhaque.github.io/) at _**haque.k@northeastern.edu** |
