Junqing Zhang

Junqing Zhang

A passionate wireless security researcher at University of Liverpool

Publication - Radio Frequency Fingerprint Identification @ University of Liverpool

Published:

  • denotes corresponding author.

Dataset

  1. Dataset: LoRa RFFI

    Guanxiong Shen, Junqing Zhang*, Alan Marshall, and Joseph Cavallaro, “Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa,” IEEE Transactions on Information Forensics and Security, vol. 17, pp. 774 - 787, Feb. 2022. IEEE, arXiv

  2. Dataset: LoRa RFFI with Different Spreading Factors

    Guanxiong Shen, Junqing Zhang*, Alan Marshall, Mikko Valkama, and Joseph Cavallaro, “Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2355 - 2367, Apr. 2023. IEEE, arXiv link

Code

  1. Code: LoRa RFFI

    Guanxiong Shen, Junqing Zhang*, Alan Marshall, and Joseph Cavallaro, “Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa,” IEEE Transactions on Information Forensics and Security, vol. 17, pp. 774 - 787, Feb. 2022. IEEE, arXiv

  2. Code: LoRa RFFI with Different Spreading Factors

    Guanxiong Shen, Junqing Zhang*, Alan Marshall, Mikko Valkama, and Joseph Cavallaro, “Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2355 - 2367, Apr. 2023. IEEE, arXiv link

Preprint

Survey/Tutorial

  1. Lingnan Xie, Linning Pleng, Junqing Zhang and Aiqun Hu, “Radio frequency fingerprint identification for Internet of Things: A survey”, Security and Safety, vol. 3, article number. 2023022. link
  2. Junqing Zhang*, Guanxiong Shen, Walid Saad, and Kaushik Chowdhury, “Radio Frequency Fingerprint Identification for Device Authentication in the Internet of Things,” IEEE Communications Magazine, IEEE
  3. Guanxiong Shen, Junqing Zhang*, and Alan Marshall, “Deep Learning-Powered Radio Frequency Fingerprint Identification: Methodology and Case Study,” IEEE Communications Magazine, IEEE
  4. Junqing Zhang, Chip Hong Chang, Chongyan Gu, and Lajos Hanzo, “Radio Frequency Fingerprints vs. Physical Unclonable Functions - Are They Twins, Competitors or Allies?,” IEEE Network, accepted, link
  5. Junqing Zhang, Sekhar Rajendran, Zhi Sun, Roger Woods, and Lajos Hanzo, “Physical Layer Security for the Internet of Things: Authentication and Key Generation,” IEEE Wireless Communications, vol. 26, no. 5, pp. 92 - 98, Oct. 2019. link

Journal Article

  1. Guanxiong Shen, Junqing Zhang*, Alan Marshall, Roger Woods, Joseph Cavallaro, and Liquan Chen, “Towards Receiver-Agnostic and Collaborative Radio Frequency Fingerprint Identification”, IEEE Transactions on Mobile Computing, IEEE, arXiv link
  2. Guanxiong Shen, and Junqing Zhang*, “Exploration of transferable deep learning-aided radio frequency fingerprint identification systems”, Security and Safety, vol. 3, article number. 2023019. link
  3. Guanxiong Shen, Junqing Zhang*, Alan Marshall, Mikko Valkama, and Joseph Cavallaro, “Towards Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification,” IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2355 - 2367, Apr. 2023. IEEE, arXiv link
  4. Yuexiu Xing, Aiqun Hu, Junqing Zhang, Linning Peng, and Xianbin Wang, “Design of A Channel Robust Radio Frequency Fingerprint Identification Scheme,” IEEE Internet of Things Journal, vol. 10, no. 8, pp. 6946-6959, Apr. 2023. accepted link
  5. Yuepei Li, Yuan Ding, Junqing Zhang, George Goussetis, and Symon K. Podilchak, “Radio Frequency Fingerprinting Exploiting Non-Linear Memory Effect,” IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 4, pp. 1618 - 1631, Dec. 2022. link
  6. Guanxiong Shen, Junqing Zhang*, Alan Marshall, and Joseph Cavallaro, “Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa,” IEEE Transactions on Information Forensics and Security, vol. 17, pp. 774 - 787, Feb. 2022. IEEE, arXiv, Dataset, code at github
  7. Junqing Zhang, Roger Woods, Magnus Sandell, Mikko Valkama, Alan Marshall, and Joseph Cavallaro, “Radio Frequency Fingerprint Identification for Narrowband Systems, Modelling and Classification,” IEEE Transactions on Information Forensics and Security, vol. 16, pp. 3974 - 3987, 2021. link
  8. Guanxiong Shen, Junqing Zhang*, Alan Marshall, Linning Peng, and Xianbin Wang, “Radio Frequency Fingerprint Identification for LoRa Using Deep Learning,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 8, pp. 2604 - 2616, Aug. 2021. link
  9. Xintao Huan, Kyeong Soo Kim, and Junqing Zhang,“NISA: Node Identification and Spoofing Attack Detection Based on Clock Features and Radio Information for Wireless Sensor Networks,” IEEE Transactions on Communications, vol. 69, no. 7, pp. 4691 - 4703, Jul. 2021. link
  10. Yuexiu Xing, Aiqun Hu, Junqing Zhang, Jiabao Yu, Guyue Li, and Ting Wang, “Design of a Robust Radio Frequency Fingerprint Identification Scheme for Multi-Mode LFM Radar,” IEEE Internet of Things Journal, vol. 7, no. 10, pp. 10581 - 10593, Oct. 2020. . link
  11. Linning Peng, Junqing Zhang, Ming Liu and Aiqun Hu, “Deep Learning Based RF Fingerprint Identification Using Differential Constellation Trace Figure,” IEEE Transactions on Vehicular Technology, vol. 69, no. 1, pp. 1091 - 1095, Jan. 2020 link
  12. Linning Peng, Aiqun Hu, Junqing Zhang, Yu Jiang, Jiabao Yu, and Yan 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. link
  13. Yuexiu Xing, Aiqun Hu, Junqing Zhang, Linning Peng, and Guyue Li, “On radio frequency fingerprint identification for DSSS systems in low SNR scenarios,” IEEE Communications Letters, vol. 22, no. 11, pp. 2326 -2329, Nov., 2018. link

Conference Paper

  1. Min Wang, Linning Peng, Lingnan Xie, Junqing Zhang, Ming Liu, and Hua Fu, “Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method”, in Proc. IEEE INFOCOM Workshop, 2024.
  2. Tianya Zhao, Xuyu Wang, Junqing Zhang, and Shiwen Mao, “Explanation-Guided Backdoor Attacks on Model-Agnostic RF Fingerprinting,” in Proc. IEEE INFOCOM, 2024.
  3. Chen Chen, and Junqing 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, 2024.
  4. Chuanting Zhang, Shuping Dang, Junqing Zhang, Haixia Zhang, and Mark A. Beach, “Federated Radio Frequency Fingerprinting with Model Transfer and Adaptation”, in Proc. IEEE INFOCOM Workshop, 2023. link
  5. Yuexiu Xing, Xiaoxing Chen, Junqing Zhang, Aiqun Hu, and Dengyin Zhang, “A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices”, in Proc. IEEE INFOCOM Workshop, 2023.
  6. Jie Ma, Junqing Zhang, Guanxiong Shen, Alan Marshall, and Chip-Hong Chang, “White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification”, in Proc. IEEE ICC, 2023
  7. Hongyi Luo, Guyue Li, Yuexiu Xing, Junqing Zhang, Aiqun Hu, and Xianbin Wang, “RelativeRFF: Multi-Antenna Device Identification in Multipath Propagation Scenarios”, in Proc. IEEE ICC, 2023
  8. Yanjin Qiu, Linning Peng, Junqing Zhang, Ming Liu, Hua Fu, and Aiqun Hu, “Signal-independent RFF Identification for LTE Mobile Devices via Ensemble Deep Learning,”, in Proc. IEEE GLOBECOM, 2022
  9. Yuxuan Xu, Ming Liu, Linning Peng, Junqing Zhang, and Yawen Zheng, “Colluding RF Fingerprint Impersonation Attack Based on Generative Adversarial Network”, in Proc. IEEE ICC, 2022
  10. Guanxiong Shen, Junqing Zhang, Alan Marshall, Mikko Valkama, and Joseph Cavallaro, “Radio Frequency Fingerprint Identification for Security in Low-Cost IoT Devices”, in Proc. Asilomar, 2021, arXiv link, IEEE link
  11. Yuepei Li, Yuan Ding, George Goussetis, and Junqing Zhang, “Power Amplifier enabled RF Fingerprint Identification,” in Proc. IEEE Texas Symposium on Wireless and Microwave Circuits and Systems, 2021.
  12. Guanxiong Shen, Junqing Zhang, Alan Marshall, Linning Peng, and Xianbin Wang, “Radio Frequency Fingerprint Identification for LoRa Using Spectrogram and CNN,” in Proc. IEEE INFOCOM, 2021. link

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