Publications

My citation profile is available on Google Scholar.

  • Our publications on key generation from wireless channels are summarised Related page.
  • Our publications on radio-frequency fingerprint identification are summarised Related page.
  • Our publications on physical-layer authentication are summarised Related page.
  • Our publications on Wi-Fi sensing are summarised Related page.

Please email me if you require a copy of a paper.

Selected Publications

  1. 2026
    S. Gao, J. Zhang, L. Mei, S. Wang, and X. Wang, “Exploring Spatial-Temporal Representation via Star Graph for mmWave Radar-based Human Activity Recognition,” IEEE Transactions on Mobile Computing, vol. 25, no. 4, pp. 5700–5715, 2026, doi: 10.1109/tmc.2025.3634221.
    DOI arXiv 
    @article{gao2025exploring,
  title = {Exploring Spatial-Temporal Representation via Star Graph for mmWave Radar-based Human Activity Recognition},
  author = {Gao, Senhao and Zhang, Junqing and Mei, Luoyu and Wang, Shuai and Wang, Xuyu},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {25},
  number = {4},
  pages = {5700--5715},
  year = {2026},
  doi = {10.1109/tmc.2025.3634221},
  arxiv = {2512.12013},
  keywords = {mmwave-radar}
}
  2. 2025
    Y. Guo, J. Zhang, and Y.-W. P. Hong, “Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 9305–9317, 2025, doi: 10.1109/tifs.2025.3602265.
    DOI arXiv 
    @article{guo2025practical,
  title = {Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach},
  author = {Guo, Yijia and Zhang, Junqing and Hong, Y-W Peter},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {9305 - 9317},
  year = {2025},
  doi = {10.1109/tifs.2025.3602265},
  arxiv = {2508.20861},
  keywords = {phy-auth}
}
  3. 2024
    G. Yin, J. Zhang, G. Shen, and Y. Chen, “FewSense, Towards a Scalable and Cross-Domain Wi-Fi Sensing System Using Few-Shot Learning,” IEEE Transactions on Mobile Computing, vol. 23, no. 1, pp. 453–468, 2024, doi: 10.1109/tmc.2022.3221902.
    DOI arXiv 
    @article{yin2022fewsense,
  title = {{FewSense}, Towards a Scalable and Cross-Domain {Wi-Fi} Sensing System Using Few-Shot Learning},
  author = {Yin, Guolin and Zhang, Junqing and Shen, Guanxiong and Chen, Yingying},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {23},
  number = {1},
  pages = {453 - 468},
  year = {2024},
  doi = {10.1109/tmc.2022.3221902},
  arxiv = {2203.02014},
  keywords = {wifi-sensing}
}
  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}
}
  5. 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}
}

Refereed Journal Articles

  1. 2026
    Y. Guo, J. Zhang, Y.-W. P. Hong, and S. Tomasin, “Model-Driven Learning-Based Physical Layer Authentication for Mobile Wi-Fi Devices,” IEEE Transactions on Information Forensics and Security, vol. 21, pp. 1497–1511, 2026, doi: 10.1109/tifs.2026.3657184.
    DOI arXiv 
    @article{guo2026model,
  title = {Model-Driven Learning-Based Physical Layer Authentication for Mobile Wi-Fi Devices},
  author = {Guo, Yijia and Zhang, Junqing and Hong, Y-W Peter and Tomasin, Stefano},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {21},
  pages = {1497--1511},
  year = {2026},
  doi = {10.1109/tifs.2026.3657184},
  arxiv = {2603.19972},
  keywords = {phy-auth}
}
  2. 2026
    J. Ma, J. Zhang, G. Shen, A. Marshall, and C.-H. Chang, “Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification,” IEEE Transactions on Mobile Computing, vol. 25, no. 6, pp. 7831–7844, 2026, doi: 10.1109/tmc.2025.3646257.
    DOI arXiv 
    @article{ma2025adversarial,
  title = {Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Marshall, Alan and Chang, Chip-Hong},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {25},
  number = {6},
  pages = {7831--7844},
  year = {2026},
  doi = {10.1109/tmc.2025.3646257},
  arxiv = {2512.12002},
  keywords = {rffi, lora}
}
  3. 2026
    H. Fu, L. Peng, J. Zhang, M. Liu, X. Chen, and A. Hu, “Towards a Practical Key Generation System for V2X Communications,” IEEE Transactions on Mobile Computing, vol. 25, no. 5, pp. 6836–6849, 2026, doi: 10.1109/tmc.2025.3640580.
    DOI 
    @article{fu2025towards,
  title = {Towards a Practical Key Generation System for V2X Communications},
  author = {Fu, Hua and Peng, Linning and Zhang, Junqing and Liu, Ming and Chen, Xudong and Hu, Aiqun},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {25},
  number = {5},
  pages = {6836--6849},
  year = {2026},
  doi = {10.1109/tmc.2025.3640580},
  keywords = {keygen}
}
  4. 2026
    S. Gao, J. Zhang, L. Mei, S. Wang, and X. Wang, “Exploring Spatial-Temporal Representation via Star Graph for mmWave Radar-based Human Activity Recognition,” IEEE Transactions on Mobile Computing, vol. 25, no. 4, pp. 5700–5715, 2026, doi: 10.1109/tmc.2025.3634221.
    DOI arXiv 
    @article{gao2025exploring,
  title = {Exploring Spatial-Temporal Representation via Star Graph for mmWave Radar-based Human Activity Recognition},
  author = {Gao, Senhao and Zhang, Junqing and Mei, Luoyu and Wang, Shuai and Wang, Xuyu},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {25},
  number = {4},
  pages = {5700--5715},
  year = {2026},
  doi = {10.1109/tmc.2025.3634221},
  arxiv = {2512.12013},
  keywords = {mmwave-radar}
}
  5. 2026
    T. Zhao, J. Zhang, J. Dai, X. Sun, and X. Wang, “Unveiling the Threat: Data-Free Backdoor Attacks on Pre-Trained Models for RF Fingerprinting,” IEEE Transactions on Mobile Computing, vol. 25, no. 4, pp. 5421–5433, 2026, doi: 10.1109/tmc.2025.3628527.
    DOI 
    @article{zhao2025unveiling,
  title = {Unveiling the Threat: Data-Free Backdoor Attacks on Pre-Trained Models for RF Fingerprinting},
  author = {Zhao, Tianya and Zhang, Junqing and Dai, Jun and Sun, Xiaoyan and Wang, Xuyu},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {25},
  number = {4},
  pages = {5421--5433},
  year = {2026},
  doi = {10.1109/tmc.2025.3628527},
  publisher = {IEEE},
  keywords = {rffi}
}
  6. 2026
    T. T. An et al., “Quantum-Assisted Memory-Efficient Training for Parameter-Intensive Wi-Fi-Based Human Activity Recognition,” IEEE Transactions on Network Science and Engineering, 2026.
    arXiv 
    @article{an2026quantum,
  title = {Quantum-Assisted Memory-Efficient Training for Parameter-Intensive {Wi-Fi}-Based Human Activity Recognition},
  author = {An, To Truong and Zhang, Jie and Yin, Guolin and Zhang, Junqing and Li, Yanjiao and Duong, Trung Q and Cotton, Simon L},
  journal = {IEEE Transactions on Network Science and Engineering},
  year = {2026},
  arxiv = {2609.04271},
  publisher = {IEEE}
}
  7. 2026
    T. T. An, G. Yin, J. Zhang, Y. Ding, T. Q. Duong, and S. L. Cotton, “A Quantum-Optimized Training Framework for Radio Frequency Fingerprint Identification,” IEEE Journal on Selected Areas in Communications, 2026.
    @article{an2026quantumrffi,
  title = {A Quantum-Optimized Training Framework for Radio Frequency Fingerprint Identification},
  author = {An, To Truong and Yin, Guolin and Zhang, Junqing and Ding, Yuan and Duong, Trung Q and Cotton, Simon L},
  journal = {IEEE Journal on Selected Areas in Communications},
  year = {2026},
  publisher = {IEEE}
}
  8. 2026
    L. Xie, L. Peng, and J. Zhang, “Toward Channel-Robust RF Fingerprint Identification Using Spectrum Averaging and High-Order Difference,” IEEE Transactions on Information Forensics and Security, 2026.
    @article{xie2026toward,
  title = {Toward Channel-Robust {RF} Fingerprint Identification Using Spectrum Averaging and High-Order Difference},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing},
  journal = {IEEE Transactions on Information Forensics and Security},
  year = {2026},
  publisher = {IEEE},
  keywords = {rffi,wifi}
}
  9. 2025
    T. Zhao, J. Zhang, S. Mao, and X. Wang, “Explanation-Guided Backdoor Attacks Against Model-Agnostic RF Fingerprinting Systems,” IEEE Transactions on Mobile Computing, vol. 24, no. 3, pp. 2029–2042, 2025, doi: 10.1109/tmc.2024.3487967.
    DOI 
    @article{zhao2024tmc,
  title = {Explanation-Guided Backdoor Attacks Against Model-Agnostic {RF} Fingerprinting Systems},
  author = {Zhao, Tianya and Zhang, Junqing and Mao, Shiwen and Wang, Xuyu},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {24},
  number = {3},
  pages = {2029 - 2042},
  year = {2025},
  doi = {10.1109/tmc.2024.3487967},
  keywords = {rffi}
}
  10. 2025
    Y. Li, S. K. Podilchak, J. Zhang, S. L. Cotton, T. Ratnarajah, and Y. Ding, “RFFI Protocols Using Antenna Mutual Coupling and Power Amplifier Nonlinear Memory Effects,” IEEE Communications Letters, vol. 29, no. 6, pp. 1250–1254, 2025, doi: 10.1109/lcomm.2025.3558555.
    DOI 
    @article{li2025rffi,
  title = {{RFFI} Protocols Using Antenna Mutual Coupling and Power Amplifier Nonlinear Memory Effects},
  author = {Li, Yuepei and Podilchak, Symon K and Zhang, Junqing and Cotton, Simon L and Ratnarajah, Tharmalingam and Ding, Yuan},
  journal = {IEEE Communications Letters},
  volume = {29},
  number = {6},
  pages = {1250 - 1254},
  year = {2025},
  doi = {10.1109/lcomm.2025.3558555},
  keywords = {rffi}
}
  11. 2025
    G. Yin, J. Zhang, X. Yi, and X. Wang, “Evasion Attacks and Countermeasures in Deep Learning-Based Wi-Fi Gesture Recognition,” IEEE Transactions on Mobile Computing, vol. 24, no. 9, pp. 8180–8195, 2025, doi: 10.1109/tmc.2025.3557757.
    DOI 
    @article{yin2025evasion,
  title = {Evasion Attacks and Countermeasures in Deep Learning-Based {Wi-Fi} Gesture Recognition},
  author = {Yin, Guolin and Zhang, Junqing and Yi, Xinping and Wang, Xuyu},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {24},
  number = {9},
  pages = {8180 - 8195},
  year = {2025},
  doi = {10.1109/tmc.2025.3557757},
  keywords = {wifi-sensing}
}
  12. 2025
    Z. Wei, W. Hu, J. Zhang, W. Guo, and J. McCann, “Explainable Adversarial Learning Framework on Physical Layer Key Generation Combating Malicious Reconfigurable Intelligent Surface,” IEEE Transactions on Wireless Communications, vol. 24, no. 4, pp. 3529–3545, 2025, doi: 10.1109/twc.2025.3531799.
    DOI arXiv 
    @article{wei2025explainable,
  title = {Explainable Adversarial Learning Framework on Physical Layer Key Generation Combating Malicious Reconfigurable Intelligent Surface},
  author = {Wei, Zhuangkun and Hu, Wenxiu and Zhang, Junqing and Guo, Weisi and McCann, Julie},
  journal = {IEEE Transactions on Wireless Communications},
  volume = {24},
  number = {4},
  pages = {3529 - 3545},
  year = {2025},
  doi = {10.1109/twc.2025.3531799},
  arxiv = {2402.06663},
  keywords = {keygen}
}
  13. 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}
}
  14. 2025
    Y. Guo, J. Zhang, and Y.-W. P. Hong, “Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 9305–9317, 2025, doi: 10.1109/tifs.2025.3602265.
    DOI arXiv 
    @article{guo2025practical,
  title = {Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach},
  author = {Guo, Yijia and Zhang, Junqing and Hong, Y-W Peter},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {9305 - 9317},
  year = {2025},
  doi = {10.1109/tifs.2025.3602265},
  arxiv = {2508.20861},
  keywords = {phy-auth}
}
  15. 2025
    T. Lu, L. Chen, J. Zhang, C. Chen, T. Q. Duong, and M. Matthaiou, “Precoding Design for Key Generation in Extremely Large-Scale MIMO Near-Field Multi-User Systems,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 10572–10587, 2025, doi: 10.1109/tifs.2025.3614468.
    DOI 
    @article{lu2025precoding,
  title = {Precoding Design for Key Generation in Extremely Large-Scale {MIMO} Near-Field Multi-User Systems},
  author = {Lu, Tianyu and Chen, Liquan and Zhang, Junqing and Chen, Chen and Duong, Trung Q and Matthaiou, Michail},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {10572 - 10587},
  year = {2025},
  doi = {10.1109/tifs.2025.3614468},
  keywords = {keygen}
}
  16. 2025
    L. Xie, L. Peng, J. Zhang, A. Gao, H. Fu, and J. Shi, “Channel2Channel: Towards Robust Radio Frequency Fingerprint Extraction and Identification,” IEEE Journal on Selected Areas in Communications, vol. 43, no. 11, pp. 3737–3751, 2025, doi: 10.1109/jsac.2025.3584434.
    DOI 
    @article{xie2025channel2channel,
  title = {Channel2Channel: Towards Robust Radio Frequency Fingerprint Extraction and Identification},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing and Gao, Ang and Fu, Hua and Shi, Junxian},
  journal = {IEEE Journal on Selected Areas in Communications},
  volume = {43},
  number = {11},
  pages = {3737 - 3751},
  year = {2025},
  doi = {10.1109/jsac.2025.3584434},
  keywords = {rffi, wifi}
}
  17. 2025
    T. Lu, L. Chen, J. Zhang, and T. Q. Duong, “Multi-User Key Rate Optimization for Near-Field Extremely Large-Scale Antenna Array Communications,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 7982–7997, 2025, doi: 10.1109/tifs.2025.3594198.
    DOI 
    @article{lu2025multi,
  title = {Multi-User Key Rate Optimization for Near-Field Extremely Large-Scale Antenna Array Communications},
  author = {Lu, Tianyu and Chen, Liquan and Zhang, Junqing and Duong, Trung Q},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {7982 - 7997},
  year = {2025},
  doi = {10.1109/tifs.2025.3594198},
  keywords = {keygen}
}
  18. 2025
    J. Ma, J. Zhang, G. Shen, L. Peng, and A. Marshall, “Towards Channel-Robust and Receiver-Independent Radio Frequency Fingerprint Identification,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 12112–12125, 2025, doi: 10.1109/tifs.2025.3630316.
    DOI arXiv 
    @article{ma2025tifs,
  title = {Towards Channel-Robust and Receiver-Independent Radio Frequency Fingerprint Identification},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Peng, Linning and Marshall, Alan},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {12112 - 12125},
  year = {2025},
  doi = {10.1109/tifs.2025.3630316},
  arxiv = {2512.12070},
  keywords = {rffi,lora}
}
  19. 2025
    T. Lu, L. Chen, J. Zhang, W. Zhang, and M. Matthaiou, “Polar-domain multi-user key generation in near-field communications,” IEEE Transactions on Information Forensics and Security, vol. 20, pp. 11311–11325, 2025, doi: 10.1109/tifs.2025.3622317.
    DOI 
    @article{lu2025polar,
  title = {Polar-domain multi-user key generation in near-field communications},
  author = {Lu, Tianyu and Chen, Liquan and Zhang, Junqing and Zhang, Weicheng and Matthaiou, Michail},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {20},
  pages = {11311 - 11325},
  year = {2025},
  doi = {10.1109/tifs.2025.3622317}
}
  20. 2024
    G. Yin, J. Zhang, G. Shen, and Y. Chen, “FewSense, Towards a Scalable and Cross-Domain Wi-Fi Sensing System Using Few-Shot Learning,” IEEE Transactions on Mobile Computing, vol. 23, no. 1, pp. 453–468, 2024, doi: 10.1109/tmc.2022.3221902.
    DOI arXiv 
    @article{yin2022fewsense,
  title = {{FewSense}, Towards a Scalable and Cross-Domain {Wi-Fi} Sensing System Using Few-Shot Learning},
  author = {Yin, Guolin and Zhang, Junqing and Shen, Guanxiong and Chen, Yingying},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {23},
  number = {1},
  pages = {453 - 468},
  year = {2024},
  doi = {10.1109/tmc.2022.3221902},
  arxiv = {2203.02014},
  keywords = {wifi-sensing}
}
  21. 2024
    C. Chen, J. Zhang, T. Lu, M. Sandell, and L. Chen, “Secret key generation for IRS-assisted multi-antenna systems: A machine learning-based approach,” IEEE Transactions on Information Forensics and Security, vol. 19, pp. 1086–1098, 2024, doi: 10.1109/tifs.2023.3331588.
    DOI arXiv 
    @article{chen2023secret,
  title = {Secret key generation for {IRS}-assisted multi-antenna systems: A machine learning-based approach},
  author = {Chen, Chen and Zhang, Junqing and Lu, Tianyu and Sandell, Magnus and Chen, Liquan},
  journal = {IEEE Transactions on Information Forensics and Security},
  volume = {19},
  pages = {1086--1098},
  year = {2024},
  doi = {10.1109/tifs.2023.3331588},
  arxiv = {2305.00043},
  keywords = {keygen}
}
  22. 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 
    @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}
}
  23. 2024
    X. Zhang, G. Li, J. Zhang, L. Peng, A. Hu, and X. Wang, “Enabling deep learning-based physical-layer secret key generation for FDD-OFDM systems in multi-environments,” IEEE Transactions on Vehicular Technology, vol. 73, no. 7, pp. 10135–10149, 2024, doi: 10.1109/tvt.2024.3367362.
    DOI arXiv 
    @article{zhang2024enabling,
  title = {Enabling deep learning-based physical-layer secret key generation for {FDD-OFDM} systems in multi-environments},
  author = {Zhang, Xinwei and Li, Guyue and Zhang, Junqing and Peng, Linning and Hu, Aiqun and Wang, Xianbin},
  journal = {IEEE Transactions on Vehicular Technology},
  volume = {73},
  number = {7},
  pages = {10135 - 10149},
  year = {2024},
  doi = {10.1109/tvt.2024.3367362},
  arxiv = {2211.03065},
  keywords = {keygen}
}
  24. 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}
}
  25. 2024
    G. Shen and J. Zhang, “Exploration of transferable deep learning-aided radio frequency fingerprint identification systems,” Security and Safety, vol. 3, p. 2023019, 2024, doi: 10.1051/sands/2023019.
    DOI 
    @article{shen2024exploration,
  title = {Exploration of transferable deep learning-aided radio frequency fingerprint identification systems},
  author = {Shen, Guanxiong and Zhang, Junqing},
  journal = {Security and Safety},
  volume = {3},
  pages = {2023019},
  year = {2024},
  doi = {10.1051/sands/2023019},
  publisher = {EDP Sciences and CSPM},
  keywords = {rffi,lora}
}
  26. 2024
    G. Li, Y. Ma, W. Wang, J. Zhang, and H. Luo, “The Self-Detection Method of the Puppet Attack in Biometric Fingerprinting,” IEEE Internet of Things Journal, vol. 11, no. 10, pp. 18824–18838, 2024, doi: 10.1109/jiot.2024.3365714.
    DOI 
    @article{li2024self,
  title = {The Self-Detection Method of the Puppet Attack in Biometric Fingerprinting},
  author = {Li, Guyue and Ma, Yiyun and Wang, Wenhao and Zhang, Junqing and Luo, Hongyi},
  journal = {IEEE Internet of Things Journal},
  volume = {11},
  number = {10},
  pages = {18824 - 18838},
  year = {2024},
  doi = {10.1109/jiot.2024.3365714}
}
  27. 2024
    L. Peng, Z. Wu, J. Zhang, M. Liu, H. Fu, and A. Hu, “Hybrid RFF Identification for LTE Using Wavelet Coefficient Graph and Differential Spectrum,” IEEE Transactions on Vehicular Technology, vol. 73, no. 8, pp. 11621–11636, 2024, doi: 10.1109/tvt.2024.3380671.
    DOI 
    @article{peng2024hybrid,
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  title = {Design of an efficient {OFDMA}-based multi-user key generation protocol},
  author = {Zhang, Junqing and Ding, Ming and L{\'o}pez-P{\'e}rez, David and Marshall, Alan and Hanzo, Lajos},
  journal = {IEEE Transactions on Vehicular Technology},
  volume = {68},
  number = {9},
  pages = {8842--8852},
  year = {2019},
  doi = {10.1109/tvt.2019.2929362},
  keywords = {keygen}
}
  61. 2019
    L. Peng, A. Hu, J. Zhang, Y. Jiang, J. Yu, and Y. Yan, “Design of a hybrid RF fingerprint extraction and device classification scheme,” IEEE Internet of Things Journal, vol. 6, no. 1, pp. 349–360, 2019, doi: 10.1109/jiot.2018.2838071.
    DOI 
    @article{peng2018design,
  title = {Design of a hybrid {RF} fingerprint extraction and device classification scheme},
  author = {Peng, Linning and Hu, Aiqun and Zhang, Junqing and Jiang, Yu and Yu, Jiabao and Yan, Yan},
  journal = {IEEE Internet of Things Journal},
  volume = {6},
  number = {1},
  pages = {349--360},
  year = {2019},
  doi = {10.1109/jiot.2018.2838071},
  keywords = {rffi,,zigbee}
}
  62. 2019
    L. Peng, G. Li, J. Zhang, R. Woods, M. Liu, and A. Hu, “An investigation of using loop-back mechanism for channel reciprocity enhancement in secret key generation,” IEEE Transactions on Mobile Computing, vol. 18, no. 3, pp. 507–519, 2019, doi: 10.1109/tmc.2018.2842215.
    DOI 
    @article{linning2018investigation,
  title = {An investigation of using loop-back mechanism for channel reciprocity enhancement in secret key generation},
  author = {Peng, Linning and Li, Guyue and Zhang, Junqing and Woods, Roger and Liu, Ming and Hu, Aiqun},
  journal = {IEEE Transactions on Mobile Computing},
  volume = {18},
  number = {3},
  pages = {507--519},
  year = {2019},
  doi = {10.1109/tmc.2018.2842215},
  keywords = {keygen}
}
  63. 2018
    G. Li, A. Hu, J. Zhang, L. Peng, C. Sun, and D. Cao, “High-agreement uncorrelated secret key generation based on principal component analysis preprocessing,” IEEE Transactions on Communications, vol. 66, no. 7, pp. 3022–3034, 2018, doi: 10.1109/tcomm.2018.2814607.
    DOI 
    @article{li2018high,
  title = {High-agreement uncorrelated secret key generation based on principal component analysis preprocessing},
  author = {Li, Guyue and Hu, Aiqun and Zhang, Junqing and Peng, Linning and Sun, Chen and Cao, Daming},
  journal = {IEEE Transactions on Communications},
  volume = {66},
  number = {7},
  pages = {3022--3034},
  year = {2018},
  doi = {10.1109/tcomm.2018.2814607},
  keywords = {keygen}
}
  64. 2018
    Y. Xing, A. Hu, J. Zhang, L. Peng, and G. Li, “On radio frequency fingerprint identification for DSSS systems in low SNR scenarios,” IEEE Communications Letters, vol. 22, no. 11, pp. 2326–2329, 2018, doi: 10.1109/lcomm.2018.2871454.
    DOI 
    @article{xing2018radio,
  title = {On radio frequency fingerprint identification for {DSSS} systems in low {SNR} scenarios},
  author = {Xing, Yuexiu and Hu, Aiqun and Zhang, Junqing and Peng, Linning and Li, Guyue},
  journal = {IEEE Communications Letters},
  volume = {22},
  number = {11},
  pages = {2326--2329},
  year = {2018},
  doi = {10.1109/lcomm.2018.2871454},
  keywords = {rffi,zigbee}
}
  65. 2018
    G. Li, A. Hu, C. Sun, and J. Zhang, “Constructing reciprocal channel coefficients for secret key generation in FDD systems,” IEEE Communications Letters, vol. 22, no. 12, pp. 2487–2490, 2018, doi: 10.1109/lcomm.2018.2875708.
    DOI 
    @article{li2018constructing,
  title = {Constructing reciprocal channel coefficients for secret key generation in {FDD} systems},
  author = {Li, Guyue and Hu, Aiqun and Sun, Chen and Zhang, Junqing},
  journal = {IEEE Communications Letters},
  volume = {22},
  number = {12},
  pages = {2487--2490},
  year = {2018},
  doi = {10.1109/lcomm.2018.2875708},
  keywords = {keygen}
}
  66. 2018
    J. Zhang, A. Marshall, and L. Hanzo, “Channel-envelope differencing eliminates secret key correlation: LoRa-based key generation in low power wide area networks,” IEEE Transactions on Vehicular Technology, vol. 67, no. 12, pp. 12462–12466, 2018, doi: 10.1109/tvt.2018.2877201.
    DOI arXiv 
    @article{zhang2018channel,
  title = {Channel-envelope differencing eliminates secret key correlation: {LoRa}-based key generation in low power wide area networks},
  author = {Zhang, Junqing and Marshall, Alan and Hanzo, Lajos},
  journal = {IEEE Transactions on Vehicular Technology},
  volume = {67},
  number = {12},
  pages = {12462--12466},
  year = {2018},
  doi = {10.1109/tvt.2018.2877201},
  arxiv = {1810.08031},
  keywords = {keygen}
}
  67. 2018
    Y. Zhang, R. Woods, Y. Ko, A. Marshall, and J. Zhang, “Security optimization of exposure region-based beamforming with a uniform circular array,” IEEE Transactions on Communications, vol. 66, no. 6, pp. 2630–2641, 2018, doi: 10.1109/tcomm.2017.2768516.
    DOI 
    @article{zhang2017security,
  title = {Security optimization of exposure region-based beamforming with a uniform circular array},
  author = {Zhang, Yuanrui and Woods, Roger and Ko, Youngwook and Marshall, Alan and Zhang, Junqing},
  journal = {IEEE Transactions on Communications},
  volume = {66},
  number = {6},
  pages = {2630--2641},
  year = {2018},
  doi = {10.1109/tcomm.2017.2768516}
}
  68. 2017
    J. Zhang, A. Marshall, R. Woods, and T. Q. Duong, “Design of an OFDM physical layer encryption scheme,” IEEE Transactions on Vehicular Technology, vol. 66, no. 3, pp. 2114–2127, 2017, doi: 10.1109/tvt.2016.2571264.
    DOI 
    @article{zhang2016design,
  title = {Design of an {OFDM} physical layer encryption scheme},
  author = {Zhang, Junqing and Marshall, Alan and Woods, Roger and Duong, Trung Q},
  journal = {IEEE Transactions on Vehicular Technology},
  volume = {66},
  number = {3},
  pages = {2114--2127},
  year = {2017},
  doi = {10.1109/tvt.2016.2571264}
}
  69. 2017
    Y. Ding, J. Zhang, and V. F. Fusco, “Retrodirective-assisted secure wireless key establishment,” IEEE Transactions on Communications, vol. 65, no. 1, pp. 320–334, 2017, doi: 10.1109/tcomm.2016.2616406.
    DOI 
    @article{ding2016retrodirective,
  title = {Retrodirective-assisted secure wireless key establishment},
  author = {Ding, Yuan and Zhang, Junqing and Fusco, Vincent F},
  journal = {IEEE Transactions on Communications},
  volume = {65},
  number = {1},
  pages = {320--334},
  year = {2017},
  doi = {10.1109/tcomm.2016.2616406}
}
  70. 2017
    J. Zhang, T. Q. Duong, R. Woods, and A. Marshall, “Securing wireless communications of the Internet of things from the physical layer, An overview,” Entropy, vol. 19, no. 8, p. 420, 2017, doi: 10.3390/e19080420.
    DOI arXiv 
    @article{zhang2017securing,
  title = {Securing wireless communications of the {Internet} of things from the physical layer, An overview},
  author = {Zhang, Junqing and Duong, Trung Q and Woods, Roger and Marshall, Alan},
  journal = {Entropy},
  volume = {19},
  number = {8},
  pages = {420},
  year = {2017},
  doi = {10.3390/e19080420},
  arxiv = {1708.05124},
  keywords = {keygen,survey}
}
  71. 2017
    H. T. Nguyen, J. Zhang, N. Yang, T. Q. Duong, and W.-J. Hwang, “Secure cooperative single carrier systems under unreliable backhaul and dense networks impact,” IEEE Access, vol. 5, pp. 18310–18324, 2017, doi: 10.1109/access.2017.2727399.
    DOI 
    @article{nguyen2017secure,
  title = {Secure cooperative single carrier systems under unreliable backhaul and dense networks impact},
  author = {Nguyen, Huy T and Zhang, Junqing and Yang, Nan and Duong, Trung Q and Hwang, Won-Joo},
  journal = {IEEE Access},
  volume = {5},
  pages = {18310--18324},
  year = {2017},
  doi = {10.1109/access.2017.2727399}
}
  72. 2017
    J. Zhang, B. He, T. Q. Duong, and R. Woods, “On the key generation from correlated wireless channels,” IEEE Communications Letters, vol. 21, no. 4, pp. 961–964, 2017, doi: 10.1109/lcomm.2017.2649496.
    DOI 
    @article{zhang2017key,
  title = {On the key generation from correlated wireless channels},
  author = {Zhang, Junqing and He, Biao and Duong, Trung Q and Woods, Roger},
  journal = {IEEE Communications Letters},
  volume = {21},
  number = {4},
  pages = {961--964},
  year = {2017},
  doi = {10.1109/lcomm.2017.2649496},
  keywords = {keygen}
}
  73. 2016
    J. Zhang, A. Marshall, R. Woods, and T. Q. Duong, “Efficient key generation by exploiting randomness from channel responses of individual OFDM subcarriers,” IEEE Transactions on Communications, vol. 64, no. 6, pp. 2578–2588, 2016, doi: 10.1109/tcomm.2016.2552165.
    DOI 
    @article{zhang2016efficient,
  title = {Efficient key generation by exploiting randomness from channel responses of individual {OFDM} subcarriers},
  author = {Zhang, Junqing and Marshall, Alan and Woods, Roger and Duong, Trung Q},
  journal = {IEEE Transactions on Communications},
  volume = {64},
  number = {6},
  pages = {2578--2588},
  year = {2016},
  doi = {10.1109/tcomm.2016.2552165},
  keywords = {keygen}
}
  74. 2016
    J. Zhang, T. Q. Duong, A. Marshall, and R. Woods, “Key generation from wireless channels: A review,” IEEE Access, vol. 4, pp. 614–626, 2016, doi: 10.1109/access.2016.2521718.
    DOI 
    @article{zhang2016key,
  title = {Key generation from wireless channels: A review},
  author = {Zhang, Junqing and Duong, Trung Q and Marshall, Alan and Woods, Roger},
  journal = {IEEE Access},
  volume = {4},
  pages = {614--626},
  year = {2016},
  doi = {10.1109/access.2016.2521718},
  keywords = {keygen,survey}
}
  75. 2016
    J. Zhang, N.-P. Nguyen, J. Zhang, E. Garcia-Palacios, and N. P. Le, “Impact of primary networks on the performance of energy harvesting cognitive radio networks,” IET Communications, vol. 10, no. 18, pp. 2559–2566, 2016, doi: 10.1049/iet-com.2016.0400.
    DOI 
    @article{zhang2016impact,
  title = {Impact of primary networks on the performance of energy harvesting cognitive radio networks},
  author = {Zhang, Jinghua and Nguyen, Nam-Phong and Zhang, Junqing and Garcia-Palacios, Emiliano and Le, Ngoc Phuc},
  journal = {IET Communications},
  volume = {10},
  number = {18},
  pages = {2559--2566},
  year = {2016},
  doi = {10.1049/iet-com.2016.0400}
}
  76. 2016
    N.-S. Vo, D.-B. Ha, B. Canberk, and J. Zhang, “Green two-tiered wireless multimedia sensor systems: an energy, bandwidth, and quality optimisation framework,” IET Communications, vol. 10, no. 18, pp. 2543–2550, 2016, doi: 10.1049/iet-com.2016.0406.
    DOI 
    @article{vo2016green,
  title = {Green two-tiered wireless multimedia sensor systems: an energy, bandwidth, and quality optimisation framework},
  author = {Vo, Nguyen-Son and Ha, Dac-Binh and Canberk, Berk and Zhang, Junqing},
  journal = {IET Communications},
  volume = {10},
  number = {18},
  pages = {2543--2550},
  year = {2016},
  doi = {10.1049/iet-com.2016.0406}
}
  77. 2016
    J. Zhang et al., “Experimental study on key generation for physical layer security in wireless communications,” IEEE Access, vol. 4, pp. 4464–4477, 2016, doi: 10.1109/access.2016.2604618.
    DOI 
    @article{zhang2016experimental,
  title = {Experimental study on key generation for physical layer security in wireless communications},
  author = {Zhang, Junqing and Woods, Roger and Duong, Trung Q and Marshall, Alan and Ding, Yuan and Huang, Yi and Xu, Qian},
  journal = {IEEE Access},
  volume = {4},
  pages = {4464--4477},
  year = {2016},
  doi = {10.1109/access.2016.2604618},
  keywords = {keygen}
}
  78. 2015
    Y. Ding, J. Zhang, and V. Fusco, “Frequency diverse array OFDM transmitter for secure wireless communication,” Electronics Letters, vol. 51, no. 17, pp. 1374–1376, 2015, doi: 10.1049/el.2015.1491.
    DOI 
    @article{ding2015frequency,
  title = {Frequency diverse array {OFDM} transmitter for secure wireless communication},
  author = {Ding, Yuan and Zhang, Junqing and Fusco, Vincent},
  journal = {Electronics Letters},
  volume = {51},
  number = {17},
  pages = {1374--1376},
  year = {2015},
  doi = {10.1049/el.2015.1491}
}

Refereed Conference Proceedings

  1. 2026
    S. Wang, J. Zhang, J. Mao, A. Brighente, G. Shen, and M. Conti, “Triad-GAN: Feature-Level Generative Adversarial Network for Multi-Receiver Radio Frequency Fingerprint Identification,” in Proc. IEEE International Conference on Communications (ICC), 2026, p. 88052.
    @inproceedings{wang2026triad,
  title = {{Triad-GAN}: Feature-Level Generative Adversarial Network for Multi-Receiver Radio Frequency Fingerprint Identification},
  author = {Wang, Shuo and Zhang, Junqing and Mao, Jiahuai and Brighente, Alessandro and Shen, Guanxiong and Conti, Mauro},
  booktitle = {Proc. IEEE International Conference on Communications (ICC)},
  pages = {88052},
  year = {2026},
  keywords = {rffi,lora}
}
  2. 2026
    E. Bothereau et al., “Lightweight Preprocessing and Feature Extraction for LoRa RF Fingerprint Identification,” in Proc. IEEE International Conference on Communications (ICC), IEEE, 2026, pp. 1–6.
    @inproceedings{bothereau2026lightweight,
  title = {Lightweight Preprocessing and Feature Extraction for {LoRa RF} Fingerprint Identification},
  author = {Bothereau, Emma and Gerzaguet, Robin and Gautier, Matthieu and Zhang, Junqing and Chillet, Alice and Marshall, Alan and Berder, Olivier},
  booktitle = {Proc. IEEE International Conference on Communications (ICC)},
  pages = {1--6},
  year = {2026},
  organization = {IEEE},
  keywords = {rffi,lora}
}
  3. 2026
    Y. Guo, J. Zhang, and Y.-W. P. Hong, “Channel Prediction-Based Physical Layer Authentication under Consecutive Spoofing Attacks,” in Proc. IEEE International Conference on Communications (ICC), 2026, pp. 1–6.
    arXiv 
    @inproceedings{guo2026channel,
  title = {Channel Prediction-Based Physical Layer Authentication under Consecutive Spoofing Attacks},
  author = {Guo, Yijia and Zhang, Junqing and Hong, Y-W Peter},
  booktitle = {Proc. IEEE International Conference on Communications (ICC)},
  pages = {1--6},
  year = {2026},
  arxiv = {2603.19962},
  keywords = {phy-auth}
}
  4. 2025
    L. Xie, L. Peng, and J. Zhang, “Towards Robust RF Fingerprint Identification Using Spectral Regrowth and Carrier Frequency Offset,” in Proc. IEEE Conference on Computer Communications (INFOCOM), 2025, pp. 1–10. doi: 10.1109/infocom55648.2025.11044651.
    DOI arXiv 
    @inproceedings{xie2024towards,
  title = {Towards Robust {RF} Fingerprint Identification Using Spectral Regrowth and Carrier Frequency Offset},
  author = {Xie, Lingnan and Peng, Linning and Zhang, Junqing},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM)},
  pages = {1--10},
  year = {2025},
  doi = {10.1109/infocom55648.2025.11044651},
  arxiv = {2412.07269},
  keywords = {rffi,wifi}
}
  5. 2025
    W. Jing, L. Peng, J. Zhang, and H. Fu, “An Investigation of Power Amplifier Feature for Deep Learning Based RF Fingerprint Identification,” in Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops, 2025, pp. 1–6. doi: 10.1109/infocomwkshps65812.2025.11152961.
    DOI 
    @inproceedings{jing2025investigation,
  title = {An Investigation of Power Amplifier Feature for Deep Learning Based RF Fingerprint Identification},
  author = {Jing, Wentao and Peng, Linning and Zhang, Junqing and Fu, Hua},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops},
  pages = {1--6},
  year = {2025},
  doi = {10.1109/infocomwkshps65812.2025.11152961},
  keywords = {rffi}
}
  6. 2025
    G. Yin, J. Zhang, Y. Ding, and S. Cotton, “Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Model,” in Proc. IEEE Wireless Communications and Networking Conference Workshops, 2025, pp. 1–6. doi: 10.1109/wcnc61545.2025.10978824.
    DOI arXiv 
    @inproceedings{yin2025noise,
  title = {Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Model},
  author = {Yin, Guolin and Zhang, Junqing and Ding, Yuan and Cotton, Simon},
  booktitle = {Proc. IEEE  Wireless Communications and Networking Conference Workshops},
  pages = {1--6},
  year = {2025},
  doi = {10.1109/wcnc61545.2025.10978824},
  arxiv = {2503.05514},
  keywords = {rffi,wifi}
}
  7. 2025
    J. Ma, J. Zhang, G. Shen, L. Peng, and A. Marshall, “Towards Channel-Robust Radio Frequency Fingerprint Identification Using Contrastive Learning,” in Proc. IEEE Wireless Communications and Networking Conference, 2025, pp. 1–6. doi: 10.1109/wcnc61545.2025.10978330.
    DOI 
    @inproceedings{ma2025towards,
  title = {Towards Channel-Robust Radio Frequency Fingerprint Identification Using Contrastive Learning},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Peng, Linning and Marshall, Alan},
  booktitle = {Proc. IEEE  Wireless Communications and Networking Conference},
  pages = {1--6},
  year = {2025},
  doi = {10.1109/wcnc61545.2025.10978330},
  keywords = {rffi,lora}
}
  8. 2025
    N. Yuan, J. Zhang, Y. Ding, and S. L. Cotton, “Robust Radio Frequency Fingerprint Identification for Bluetooth Low Energy under Low SNR and Channel Variations,” in Proc. IEEE Wireless Communications and Networking Conference, 2025, pp. 01–06. doi: 10.1109/wcnc61545.2025.10978258.
    DOI 
    @inproceedings{yuan2025robust,
  title = {Robust Radio Frequency Fingerprint Identification for {Bluetooth} Low Energy under Low SNR and Channel Variations},
  author = {Yuan, Ningze and Zhang, Junqing and Ding, Yuan and Cotton, Simon L},
  booktitle = {Proc. IEEE Wireless Communications and Networking Conference},
  pages = {01--06},
  year = {2025},
  doi = {10.1109/wcnc61545.2025.10978258},
  keywords = {rffi,ble}
}
  9. 2025
    T. Zhao, N. Wang, J. Zhang, and X. Wang, “Protocol-agnostic and Data-free Backdoor Attacks on Pre-trained Models in RF Fingerprinting,” in Proc. IEEE Conference on Computer Communications (INFOCOM), 2025, pp. 1–10. doi: 10.1109/infocom55648.2025.11044704.
    DOI arXiv 
    @inproceedings{zhao2025protocol,
  title = {Protocol-agnostic and Data-free Backdoor Attacks on Pre-trained Models in RF Fingerprinting},
  author = {Zhao, Tianya and Wang, Ningning and Zhang, Junqing and Wang, Xuyu},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM)},
  pages = {1--10},
  year = {2025},
  doi = {10.1109/infocom55648.2025.11044704},
  arxiv = {2505.00881},
  keywords = {rffi}
}
  10. 2024
    M. Wang, L. Peng, L. Xie, J. Zhang, M. Liu, and H. Fu, “Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method,” in Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops, 2024, pp. 1–6. doi: 10.1109/infocomwkshps61880.2024.10620671.
    DOI 
    @inproceedings{wang2024design,
  title = {Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method},
  author = {Wang, Min and Peng, Linning and Xie, Lingnan and Zhang, Junqing and Liu, Ming and Fu, Hua},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops},
  pages = {1--6},
  year = {2024},
  doi = {10.1109/infocomwkshps61880.2024.10620671},
  keywords = {rffi,lte}
}
  11. 2024
    T. Zhao, X. Wang, J. Zhang, and S. Mao, “Explanation-guided backdoor attacks on model-agnostic RF fingerprinting,” in Proc. IEEE Conference on Computer Communications (INFOCOM), 2024, pp. 221–230. doi: 10.1109/infocom52122.2024.10621289.
    DOI 
    @inproceedings{zhao2024explanation,
  title = {Explanation-guided backdoor attacks on model-agnostic {RF} fingerprinting},
  author = {Zhao, Tianya and Wang, Xuyu and Zhang, Junqing and Mao, Shiwen},
  booktitle = {Proc. IEEE Conference on Computer Communications (INFOCOM)},
  pages = {221--230},
  year = {2024},
  doi = {10.1109/infocom52122.2024.10621289},
  keywords = {rffi}
}
  12. 2024
    C. Chen and J. Zhang, “Machine Learning Enhanced Near-Field Secret Key Generation for Extremely Large-Scale MIMO,” in Proc. IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN), 2024, pp. 183–188. doi: 10.1109/icmlcn59089.2024.10624801.
    DOI 
    @inproceedings{chen2024machine,
  title = {Machine Learning Enhanced Near-Field Secret Key Generation for Extremely Large-Scale MIMO},
  author = {Chen, Chen and Zhang, Junqing},
  booktitle = {Proc. IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN)},
  pages = {183--188},
  year = {2024},
  doi = {10.1109/icmlcn59089.2024.10624801},
  keywords = {keygen}
}
  13. 2024
    T. T. An, S. L. Cotton, J. Zhang, Y. Ding, and T. Q. Duong, “LoRa Radio Frequency Fingerprinting Using a Hybrid Quantum-Classical Neural Network,” in Proc. IEEE 100th Vehicular Technology Conference, 2024.
    @inproceedings{an2024lora,
  title = {{LoRa} Radio Frequency Fingerprinting Using a Hybrid Quantum-Classical Neural Network},
  author = {An, To Truong and Cotton, Simon L and Zhang, Junqing and Ding, Yuan and Duong, Trung Q},
  booktitle = {Proc. IEEE 100th Vehicular Technology Conference},
  year = {2024},
  keywords = {rffi,lora}
}
  14. 2023
    H. Luo, G. Li, Y. Xing, J. Zhang, A. Hu, and X. Wang, “RelativeRFF: Multi-Antenna Device Identification in Multipath Propagation Scenarios,” in Proc. IEEE ICC, 2023, pp. 3708–3713. doi: 10.1109/icc45041.2023.10279540.
    DOI 
    @inproceedings{luo2023relative,
  title = {{RelativeRFF}: Multi-Antenna Device Identification in Multipath Propagation Scenarios},
  author = {Luo, Hongyi and Li, Guyue and Xing, Yuexiu and Zhang, Junqing and Hu, Aiqun and Wang, Xianbin},
  booktitle = {Proc. IEEE ICC},
  pages = {3708--3713},
  year = {2023},
  doi = {10.1109/icc45041.2023.10279540},
  keywords = {rffi}
}
  15. 2023
    J. Ma, J. Zhang, G. Shen, A. Marshall, and C.-H. Chang, “White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification,” in Proc. IEEE ICC, 2023, pp. 3714–3719. doi: 10.1109/icc45041.2023.10278927.
    DOI arXiv 
    @inproceedings{ma2023whitebox,
  title = {White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification},
  author = {Ma, Jie and Zhang, Junqing and Shen, Guanxiong and Marshall, Alan and Chang, Chip-Hong},
  booktitle = {Proc. IEEE ICC},
  pages = {3714--3719},
  year = {2023},
  doi = {10.1109/icc45041.2023.10278927},
  arxiv = {2308.07433},
  keywords = {rffi,lora}
}
  16. 2023
    C. Chen, J. Zhang, T. Lu, M. Sandell, and L. Chen, “Machine Learning-Based Secret Key Generation for IRS-assisted Multi-antenna Systems,” in Proc. IEEE ICC, 2023, pp. 5861–5866. doi: 10.1109/icc45041.2023.10279041.
    DOI arXiv 
    @inproceedings{chen2023machine,
  title = {Machine Learning-Based Secret Key Generation for {IRS}-assisted Multi-antenna Systems},
  author = {Chen, Chen and Zhang, Junqing and Lu, Tianyu and Sandell, Magnus and Chen, Liquan},
  booktitle = {Proc. IEEE ICC},
  pages = {5861--5866},
  year = {2023},
  doi = {10.1109/icc45041.2023.10279041},
  arxiv = {2301.08179},
  keywords = {keygen}
}
  17. 2023
    T. Lu, L. Chen, J. Zhang, C. Chen, and T. Duong, “Reconfigurable Intelligent Surface-Assisted Key Generation for Millimeter Wave Communications,” in Proc. IEEE WCNC Workshop, 2023, pp. 1–6. doi: 10.1109/wcnc55385.2023.10119128.
    DOI 
    @inproceedings{chen2023ris,
  title = {Reconfigurable Intelligent Surface-Assisted Key Generation for Millimeter Wave Communications},
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  18. 2023
    Y. Guo, J. Zhang, and Y.-W. P. Hong, “Deep Learning-Enhanced Physical Layer Authentication for Mobile Devices,” in Proc. IEEE GLOBECOM, 2023, pp. 826–831. doi: 10.1109/globecom54140.2023.10437299.
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  19. 2023
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  20. 2023
    C. Zhang, S. Dang, J. Zhang, H. Zhang, and M. A. Beach, “Federated Radio Frequency Fingerprinting with Model Transfer and Adaptation,” in Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops, 2023, pp. 1–6. doi: 10.1109/infocomwkshps57453.2023.10226112.
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  21. 2023
    Y. Xing, X. Chen, J. Zhang, A. Hu, and D. Zhang, “A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices,” in Proc. IEEE Conference on Computer Communications (INFOCOM) Workshops, 2023, pp. 1–6. doi: 10.1109/infocomwkshps57453.2023.10225749.
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  22. 2022
    G. Li, H. Yang, J. Zhang, H. Liu, and A. Hu, “Fast and secure key generation with channel obfuscation in slowly varying environments,” in Proc. IEEE Conference on Computer Communications (INFOCOM), 2022, pp. 1–10. doi: 10.1109/infocom48880.2022.9796694.
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  23. 2022
    Z. Wu, L. Peng, J. Zhang, M. Liu, H. Fu, and A. Hu, “Authorized and Rogue LTE Terminal Identification Using Wavelet Coefficient Graph with Auto-encoder,” in Proc. IEEE VTC Fall, 2022, pp. 1–5. doi: 10.1109/vtc2022-fall57202.2022.10012861.
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  24. 2022
    Y. Qiu, L. Peng, J. Zhang, M. Liu, H. Fu, and A. Hu, “Signal-independent RFF Identification for LTE Mobile Devices via Ensemble Deep Learning,” in Proc. IEEE GLOBECOM, 2022, pp. 37–42. doi: 10.1109/globecom48099.2022.10000722.
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  25. 2022
    Y. Xu, M. Liu, L. Peng, J. Zhang, and Y. Zheng, “Colluding RF Fingerprint Impersonation Attack Based on Generative Adversarial Network,” in Proc. IEEE International Conference on Communications (ICC), 2022, pp. 3220–3225. doi: 10.1109/icc45855.2022.9838574.
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  26. 2021
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  27. 2021
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  28. 2021
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  29. 2021
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  30. 2020
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  31. 2019
    W. Li, M. Ghogho, J. Zhang, D. McLernon, J. Lei, and S. A. R. Zaidi, “Design of an Energy-Efficient Multidimensional Secure Constellation for 5G Communications,” in Proc. IEEE International Conference on Communications Workshops (ICC Workshops), 2019, pp. 1–6. doi: 10.1109/iccw.2019.8756862.
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  35. 2017
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  40. 2015
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  41. 2014
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