RFFI Recommended Reading List

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Survey and Tutorial Papers from Our Group

  1. 2025
    J. Zhang, F. Ardizzon, M. Piana, G. Shen, and S. Tomasin, “Physical Layer-Based Device Fingerprinting For Wireless Security: From Theory To Practice,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 5296–5325, 2025, doi: 10.1109/tifs.2025.3570118.
    DOI arXiv 
    @article{zhang2025physical,
  title = {Physical Layer-Based Device Fingerprinting For Wireless Security: From Theory To Practice},
  author = {Zhang, Junqing and Ardizzon, Francesco and Piana, Mattia and Shen, Guanxiong and Tomasin, Stefano},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {5296 - 5325},
  year = {2025},
  doi = {10.1109/tifs.2025.3570118},
  arxiv = {2506.09807},
  keywords = {rffi,phy-auth,survey}
}
  2. 2024
    L. Xie, L. Peng, J. Zhang, and A. Hu, “Radio frequency fingerprint identification for Internet of Things: A survey,” Security and Safety, vol. 3, p. 2023022, 2024, doi: 10.1051/sands/2023022.
    DOI 
    @article{xie2024radio,
  title = {Radio frequency fingerprint identification for Internet of Things: A survey},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing and Hu, Aiqun},
  journal = {Security and Safety},
  volume = {3},
  pages = {2023022},
  year = {2024},
  doi = {10.1051/sands/2023022},
  publisher = {EDP Sciences and CSPM},
  keywords = {rffi,survey}
}
  3. 2023
    J. Zhang, G. Shen, W. Saad, and K. Chowdhury, “Radio frequency fingerprint identification for device authentication in the internet of things,” IEEE Communications Magazine, vol. 61, no. 10, pp. 110–115, 2023, doi: 10.1109/mcom.003.2200974.
    DOI 
    @article{zhang2023radio,
  title = {Radio frequency fingerprint identification for device authentication in the internet of things},
  author = {Zhang, Junqing and Shen, Guanxiong and Saad, Walid and Chowdhury, Kaushik},
  journal = {IEEE Communications Magazine},
  volume = {61},
  number = {10},
  pages = {110 - 115},
  year = {2023},
  doi = {10.1109/mcom.003.2200974},
  keywords = {rffi,survey}
}
  4. 2023
    G. Shen, J. Zhang, and A. Marshall, “Deep learning-powered radio frequency fingerprint identification: Methodology and case study,” IEEE Communications Magazine, vol. 61, no. 9, pp. 170–176, 2023, doi: 10.1109/mcom.001.2200695.
    DOI 
    @article{shen2023deep,
  title = {Deep learning-powered radio frequency fingerprint identification: Methodology and case study},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan},
  journal = {IEEE Communications Magazine},
  volume = {61},
  number = {9},
  pages = {170 - 176},
  year = {2023},
  doi = {10.1109/mcom.001.2200695},
  keywords = {rffi,survey}
}
  5. 2022
    J. Zhang, C.-H. Chang, C. Gu, and L. Hanzo, “Radio Frequency Fingerprints vs. Physical Unclonable Functions-Are They Twins, Competitors or Allies?,” IEEE Network, vol. 36, no. 6, pp. 68–75, 2022, doi: 10.1109/mnet.107.2100372.
    DOI 
    @article{zhang2022radio,
  title = {Radio Frequency Fingerprints vs. Physical Unclonable Functions-Are They Twins, Competitors or Allies?},
  author = {Zhang, Junqing and Chang, Chip-Hong and Gu, Chongyan and Hanzo, Lajos},
  journal = {IEEE Network},
  volume = {36},
  number = {6},
  pages = {68 - 75},
  year = {2022},
  doi = {10.1109/mnet.107.2100372},
  keywords = {rffi,survey}
}
  6. 2019
    J. Zhang, S. Rajendran, Z. Sun, R. Woods, and L. Hanzo, “Physical layer security for the Internet of Things: Authentication and key generation,” IEEE Wireless Communications, vol. 26, no. 5, pp. 92–98, 2019, doi: 10.1109/mwc.2019.1800455.
    DOI 
    @article{zhang2019physical,
  title = {Physical layer security for the {Internet} of Things: Authentication and key generation},
  author = {Zhang, Junqing and Rajendran, Sekhar and Sun, Zhi and Woods, Roger and Hanzo, Lajos},
  journal = {IEEE Wireless Communications},
  volume = {26},
  number = {5},
  pages = {92--98},
  year = {2019},
  doi = {10.1109/mwc.2019.1800455},
  keywords = {rffi,keygen,survey}
}

Technical Papers from Our Group

LoRa RFFI

  1. 2024
    G. Shen, J. Zhang, A. Marshall, R. Woods, J. Cavallaro, and L. Chen, “Towards receiver-agnostic and collaborative radio frequency fingerprint identification,” IEEE Transactions on Mobile Computing, vol. 23, no. 7, pp. 7618–7634, 2024, doi: 10.1109/tmc.2023.3340039.
    DOI arXiv Code Data 
    @article{shen2023towards,
  title = {Towards receiver-agnostic and collaborative radio frequency fingerprint identification},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Woods, Roger and Cavallaro, Joseph and Chen, Liquan},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {23},
  number = {7},
  pages = {7618 - 7634},
  year = {2024},
  doi = {10.1109/tmc.2023.3340039},
  arxiv = {2207.02999},
  keywords = {rffi,lora, data_code}
}
  2. 2024
    G. Shen, J. Zhang, X. Wang, and S. Mao, “Federated Radio Frequency Fingerprint Identification Powered by Unsupervised Contrastive Learning,” IEEE Transactions on Information Forensics and Security, vol. 19, pp. 9204–9215, 2024, doi: 10.1109/tifs.2024.3469820.
    DOI Code Data 
    @article{shen2024federated,
  title = {Federated Radio Frequency Fingerprint Identification Powered by Unsupervised Contrastive Learning},
  author = {Shen, Guanxiong and Zhang, Junqing and Wang, Xuyu and Mao, Shiwen},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {19},
  pages = {9204 - 9215},
  year = {2024},
  doi = {10.1109/tifs.2024.3469820},
  keywords = {rffi, lora, data_code}
}
  3. 2023
    G. Shen, J. Zhang, A. Marshall, M. Valkama, and J. R. Cavallaro, “Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2355–2367, 2023, doi: 10.1109/tifs.2023.3266626.
    DOI arXiv Code Data 
    @article{shen2023length,
  title = {Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Valkama, Mikko and Cavallaro, Joseph R},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {18},
  pages = {2355 - 2367},
  year = {2023},
  doi = {10.1109/tifs.2023.3266626},
  arxiv = {2207.03001},
  keywords = {rffi,lora, data_code}
}
  4. 2022
    G. Shen, J. Zhang, A. Marshall, and J. R. Cavallaro, “Towards scalable and channel-robust radio frequency fingerprint identification for LoRa,” IEEE Transactions on Information Forensics and Security, vol. 17, pp. 774–787, 2022, doi: 10.1109/tifs.2022.3152404.
    DOI arXiv Code Data 
    @article{shen2022scalable,
  title = {Towards scalable and channel-robust radio frequency fingerprint identification for {LoRa}},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Cavallaro, Joseph R},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {17},
  pages = {774--787},
  year = {2022},
  doi = {10.1109/tifs.2022.3152404},
  arxiv = {2107.02867},
  keywords = {rffi,lora,data_code}
}
  5. 2021
    G. Shen, J. Zhang, A. Marshall, L. Peng, and X. Wang, “Radio frequency fingerprint identification for LoRa using deep learning,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 8, pp. 2604–2616, 2021, doi: 10.1109/jsac.2021.3087250.
    DOI 
    @article{shen2021radioj,
  title = {Radio frequency fingerprint identification for {LoRa} using deep learning},
  author = {Shen, Guanxiong and Zhang, Junqing and Marshall, Alan and Peng, Linning and Wang, Xianbin},
  journal = {IEEE Journal on Selected Areas in Communications},
  volume = {39},
  number = {8},
  pages = {2604--2616},
  year = {2021},
  doi = {10.1109/jsac.2021.3087250},
  keywords = {rffi,lora}
}

Modelling

  1. 2021
    J. Zhang, R. Woods, M. Sandell, M. Valkama, A. Marshall, and J. Cavallaro, “Radio frequency fingerprint identification for narrowband systems, Modelling and classification,” IEEE Transactions on Information Forensics and Security, vol. 16, pp. 3974–3987, 2021, doi: 10.1109/tifs.2021.3088008.
    DOI 
    @article{zhang2021radio,
  title = {Radio frequency fingerprint identification for narrowband systems, Modelling and classification},
  author = {Zhang, Junqing and Woods, Roger and Sandell, Magnus and Valkama, Mikko and Marshall, Alan and Cavallaro, Joseph},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {16},
  pages = {3974--3987},
  year = {2021},
  doi = {10.1109/tifs.2021.3088008},
  keywords = {rffi}
}

Tutorial Papers from Other Groups

  1. Shamnaz Riyaz, Kunal Sankhe, Stratis Ioannidis, and Kaushik Chowdhury, “Deep Learning Convolutional Neural Networks for Radio Identification,” IEEE Communications Magazine, 2018