Research outputs
Selected research outputs
- Radio Frequency Fingerprint Identification for Narrowband Systems, Modelling and Classification (Journal article - 2021)
- Radio Frequency Fingerprint Identification for LoRa Using Spectrogram and CNN (Conference Paper - 2021)
- Efficient Key Generation by Exploiting Randomness From Channel Responses of Individual OFDM Subcarriers (Journal article - 2016)
- Design of an Efficient OFDMA-Based Multi-User Key Generation Protocol (Journal article - 2019)
- H2K: A Heartbeat-Based Key Generation Framework for ECG and PPG Signals (Journal article - 2023)
2026
Model-Driven Learning-Based Physical Layer Authentication for Mobile Wi-Fi Devices
Guo, Y., Zhang, J., Hong, Y. -W. P., & Tomasin, S. (2026). Model-Driven Learning-Based Physical Layer Authentication for Mobile Wi-Fi Devices. IEEE Transactions on Information Forensics and Security, 21, 1497-1511. doi:10.1109/tifs.2026.3657184
2025
Exploring Spatial-Temporal Representation via Star Graph for mmWave Radar-based Human Activity Recognition
Gao, S., Zhang, J., Mei, L., Wang, S., & Wang, X. (2025). Exploring Spatial-Temporal Representation via Star Graph for mmWave Radar-based Human Activity Recognition. IEEE Transactions on Mobile Computing.
Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification
Ma, J., Zhang, J., Shen, G., Marshall, A., & Chang, C. -H. (2025). Adversarial Attacks Against Deep Learning-Based Radio Frequency Fingerprint Identification. IEEE Transactions on Mobile Computing, 1-14. doi:10.1109/tmc.2025.3646257
An Investigation of Power Amplifier Feature for Deep Learning Based RF Fingerprint Identification
Jing, W., Peng, L., Zhang, J., & Fu, H. (2025). An Investigation of Power Amplifier Feature for Deep Learning Based RF Fingerprint Identification. In IEEE INFOCOM 2025 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 1-6). IEEE. doi:10.1109/infocomwkshps65812.2025.11152961
Channel2Channel: Toward Robust Radio Frequency Fingerprint Extraction and Identification
Xie, L., Peng, L., Zhang, J., Gao, A., Fu, H., & Shi, J. (2025). Channel2Channel: Toward Robust Radio Frequency Fingerprint Extraction and Identification. IEEE Journal on Selected Areas in Communications, 43(11), 3737-3751. doi:10.1109/jsac.2025.3584434
Evasion Attacks and Countermeasures in Deep Learning-Based Wi-Fi Gesture Recognition
Yin, G., Zhang, J., Yi, X., & Wang, X. (2025). Evasion Attacks and Countermeasures in Deep Learning-Based Wi-Fi Gesture Recognition. IEEE Transactions on Mobile Computing, 24(9), 8180-8195. doi:10.1109/tmc.2025.3557757
Explainable Adversarial Learning Framework on Physical Layer Key Generation Combating Malicious Reconfigurable Intelligent Surface
Wei, Z., Hu, W., Zhang, J., Guo, W., & McCann, J. A. (2025). Explainable Adversarial Learning Framework on Physical Layer Key Generation Combating Malicious Reconfigurable Intelligent Surface. IEEE Transactions on Wireless Communications, 24(4), 3529-3545. doi:10.1109/twc.2025.3531799
Multi-User Key Rate Optimization for Near-Field Extremely Large-Scale Antenna Array Communications
Lu, T., Chen, L., Zhang, J., & Duong, T. Q. (2025). Multi-User Key Rate Optimization for Near-Field Extremely Large-Scale Antenna Array Communications. IEEE Transactions on Information Forensics and Security, 20, 7982-7997. doi:10.1109/tifs.2025.3594198
Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Model
Yin, G., Zhang, J., Ding, Y., & Cotton, S. (2025). Noise-Robust Radio Frequency Fingerprint Identification Using Denoise Diffusion Model. In 2025 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1-6). IEEE. doi:10.1109/wcnc61545.2025.10978824
Physical Layer-Based Device Fingerprinting for Wireless Security: From Theory to Practice
Zhang, J., Ardizzon, F., Piana, M., Shen, G., & Tomasin, S. (2025). Physical Layer-Based Device Fingerprinting for Wireless Security: From Theory to Practice. IEEE Transactions on Information Forensics and Security, 20, 5296-5325. doi:10.1109/tifs.2025.3570118
Polar-Domain Multi-User Key Generation in Near-Field Communications
Lu, T., Chen, L., Zhang, J., Zhang, W., & Matthaiou, M. (2025). Polar-Domain Multi-User Key Generation in Near-Field Communications. IEEE Transactions on Information Forensics and Security, 20, 11311-11325. doi:10.1109/tifs.2025.3622317
Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach
Guo, Y., Zhang, J., & Hong, Y. -W. P. (2025). Practical Physical Layer Authentication for Mobile Scenarios Using a Synthetic Dataset Enhanced Deep Learning Approach. IEEE Transactions on Information Forensics and Security, 20, 9305-9317. doi:10.1109/tifs.2025.3602265
Precoding Design for Key Generation in Extremely Large-Scale MIMO Near-Field Multi-User Systems
Lu, T., Chen, L., Zhang, J., Chen, C., Duong, T. Q., & Matthaiou, M. (2025). Precoding Design for Key Generation in Extremely Large-Scale MIMO Near-Field Multi-User Systems. IEEE Transactions on Information Forensics and Security, 20, 10572-10587. doi:10.1109/tifs.2025.3614468
Protocol-Agnostic and Data-Free Backdoor Attacks on Pre-Trained Models in RF Fingerprinting
Zhao, T., Wang, N., Zhang, J., & Wang, X. (2025). Protocol-Agnostic and Data-Free Backdoor Attacks on Pre-Trained Models in RF Fingerprinting. In IEEE INFOCOM 2025 - IEEE Conference on Computer Communications (pp. 1-10). IEEE. doi:10.1109/infocom55648.2025.11044704
RFFI Protocols Using Antenna Mutual Coupling and Power Amplifier Nonlinear Memory Effects
Li, Y., Podilchak, S. K., Zhang, J., Cotton, S. L., Ratnarajah, T., & Ding, Y. (2025). RFFI Protocols Using Antenna Mutual Coupling and Power Amplifier Nonlinear Memory Effects. IEEE Communications Letters, 29(6), 1250-1254. doi:10.1109/lcomm.2025.3558555
Robust Radio Frequency Fingerprint Identification for Bluetooth Low Energy Under Low SNR and Channel Variations
Yuan, N., Zhang, J., Ding, Y., & Cotton, S. (2025). Robust Radio Frequency Fingerprint Identification for Bluetooth Low Energy Under Low SNR and Channel Variations. In 2025 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 01-06). IEEE. doi:10.1109/wcnc61545.2025.10978258
Toward Channel-Robust and Receiver-Independent Radio Frequency Fingerprint Identification
Ma, J., Zhang, J., Shen, G., Peng, L., & Marshall, A. (2025). Toward Channel-Robust and Receiver-Independent Radio Frequency Fingerprint Identification. IEEE Transactions on Information Forensics and Security, 20, 12112-12125. doi:10.1109/tifs.2025.3630316
Towards Channel-Robust Radio Frequency Fingerprint Identification Using Contrastive Learning
Ma, J., Zhang, J., Shen, G., Peng, L., & Marshall, A. (2025). Towards Channel-Robust Radio Frequency Fingerprint Identification Using Contrastive Learning. In 2025 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1-6). IEEE. doi:10.1109/wcnc61545.2025.10978330
Towards Robust RF Fingerprint Identification Using Spectral Regrowth and Carrier Frequency Offset
Xie, L., Peng, L., & Zhang, J. (2025). Towards Robust RF Fingerprint Identification Using Spectral Regrowth and Carrier Frequency Offset. In IEEE INFOCOM 2025 - IEEE Conference on Computer Communications (pp. 1-10). IEEE. doi:10.1109/infocom55648.2025.11044651
Towards a Practical Key Generation System for V2X Communications
Fu, H., Peng, L., Zhang, J., Liu, M., Chen, X., & Hu, A. (2025). Towards a Practical Key Generation System for V2X Communications. IEEE Transactions on Mobile Computing, 1-14. doi:10.1109/tmc.2025.3640580
Unveiling the Threat: Data-Free Backdoor Attacks on Pre-Trained Models for RF Fingerprinting
Zhao, T., Zhang, J., Dai, J., Sun, X., & Wang, X. (2025). Unveiling the Threat: Data-Free Backdoor Attacks on Pre-Trained Models for RF Fingerprinting. IEEE Transactions on Mobile Computing, 1-13. doi:10.1109/tmc.2025.3628527
2024
Explanation-Guided Backdoor Attacks Against Model-Agnostic RF Fingerprinting Systems
Zhao, T., Zhang, J., Wang, X., & Mao, S. (2024). Explanation-Guided Backdoor Attacks Against Model-Agnostic RF Fingerprinting Systems. IEEE Transactions on Mobile Computing.
Federated Radio Frequency Fingerprint Identification Powered by Unsupervised Contrastive Learning
Shen, G., Zhang, J., Wang, X., & Mao, S. (2024). Federated Radio Frequency Fingerprint Identification Powered by Unsupervised Contrastive Learning. IEEE Transactions on Information Forensics and Security.
The Self-Detection Method of the Puppet Attack in Biometric Fingerprinting
Li, G., Ma, Y., Wang, W., Zhang, J., & Luo, H. (2024). The Self-Detection Method of the Puppet Attack in Biometric Fingerprinting. IEEE Internet of Things Journal, 11(10), 18824-18838. doi:10.1109/jiot.2024.3365714
Reconfigurable Intelligent Surface-Assisted Key Generation for Millimetre-Wave Multi-User Systems
Lu, T., Chen, L., Zhang, J., Chen, C., & Duong, T. (2024). Reconfigurable Intelligent Surface-Assisted Key Generation for Millimetre-Wave Multi-User Systems. IEEE Transactions on Information Forensics and Security.
Multi-Channel CNN-Based Open-Set RF Fingerprint Identification for LTE Devices
Yin, P., Peng, L., Shen, G., Zhang, J., Liu, M., Fu, H., . . . Wang, X. (2024). Multi-Channel CNN-Based Open-Set RF Fingerprint Identification for LTE Devices. IEEE Transactions on Cognitive Communications and Networking, 1. doi:10.1109/tccn.2024.3391293
PUF-Assisted Radio Frequency Fingerprinting Exploiting Power Amplifier Active Load-pulling
Li, Y., Xu, K., Zhang, J., Gu, C., Ding, Y., Goussetis, G., & Podilchak, S. (2024). PUF-Assisted Radio Frequency Fingerprinting Exploiting Power Amplifier Active Load-pulling. IEEE Transactions on Information Forensics and Security.
Enabling Deep Learning-based Physical-layer Secret Key Generation for FDD-OFDM Systems in Multi-Environments
Zhang, X., Li, G., Zhang, J., Peng, L., Hu, A., & Wang, X. (2024). Enabling Deep Learning-based Physical-layer Secret Key Generation for FDD-OFDM Systems in Multi-Environments. IEEE Transactions on Vehicular Technology.
Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method
Wang, M., Peng, L., Xie, L., Zhang, J., Liu, M., & Fu, H. (2024). Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method. In IEEE INFOCOM 2024 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 1-6). IEEE. doi:10.1109/infocomwkshps61880.2024.10620671
Explanation-Guided Backdoor Attacks on Model-Agnostic RF Fingerprinting
Zhao, T., Wang, X., Zhang, J., & Mao, S. (2024). Explanation-Guided Backdoor Attacks on Model-Agnostic RF Fingerprinting. In IEEE INFOCOM 2024 - IEEE Conference on Computer Communications (pp. 221-230). IEEE. doi:10.1109/infocom52122.2024.10621289
Exploration of Transferable Deep Learning-Aided Radio Frequency Fingerprint Identification Systems
Shen, G., & Zhang, J. (2023). Exploration of Transferable Deep Learning-Aided Radio Frequency Fingerprint Identification Systems. Security and Safety. doi:10.1051/sands/2023019
FewSense, Towards a Scalable and Cross-Domain Wi-Fi Sensing System Using Few-Shot Learning
Yin, G., Zhang, J., Shen, G., & Chen, Y. (2024). FewSense, Towards a Scalable and Cross-Domain Wi-Fi Sensing System Using Few-Shot Learning. IEEE Transactions on Mobile Computing, 23(1), 453-468. doi:10.1109/tmc.2022.3221902
Hybrid RFF Identification for LTE Using Wavelet Coefficient Graph and Differential Spectrum
Peng, L., Wu, Z., Zhang, J., Liu, M., Fu, H., & Hu, A. (2024). Hybrid RFF Identification for LTE Using Wavelet Coefficient Graph and Differential Spectrum. IEEE Transactions on Vehicular Technology, 73(8), 11621-11636. doi:10.1109/tvt.2024.3380671
LoRa Radio Frequency Fingerprinting Identification Using a Hybrid Quantum-Classical Neural Network
An, T. T., Cotton, S. L., Zhang, J., Ding, Y., & Duong, T. Q. (2024). LoRa Radio Frequency Fingerprinting Identification Using a Hybrid Quantum-Classical Neural Network. In 2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall) (pp. 1-6). IEEE. doi:10.1109/vtc2024-fall63153.2024.10757594
Machine Learning Enhanced Near-Field Secret Key Generation for Extremely Large-Scale MIMO
Chen, C., & Zhang, J. (2024). Machine Learning Enhanced Near-Field Secret Key Generation for Extremely Large-Scale MIMO. In 2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN) (pp. 183-188). IEEE. doi:10.1109/icmlcn59089.2024.10624801
Radio frequency fingerprint identification for Internet of Things: A survey
Xie, L., Peng, L., Zhang, J., & Hu, A. (2024). Radio frequency fingerprint identification for Internet of Things: A survey. Security and Safety, 3, 2023022. doi:10.1051/sands/2023022
Secret Key Generation for IRS-Assisted Multi-Antenna Systems: A Machine Learning-Based Approach
Chen, C., Zhang, J., Lu, T., Sandell, M., & Chen, L. (2024). Secret Key Generation for IRS-Assisted Multi-Antenna Systems: A Machine Learning-Based Approach. IEEE Transactions on Information Forensics and Security, 19, 1086-1098. doi:10.1109/tifs.2023.3331588
2023
Towards Receiver-Agnostic and Collaborative Radio Frequency Fingerprint Identification
Shen, G., Zhang, J., Marshall, A., Woods, R., Cavallaro, J., & Chen, L. (2023). Towards Receiver-Agnostic and Collaborative Radio Frequency Fingerprint Identification. IEEE Transactions on Mobile Computing. doi:10.1109/TMC.2023.3340039
Ontology of 3D virtual modeling in digital twin: a review, analysis and thinking
Wang, Y., Wang, X., Liu, A., Zhang, J., & Zhang, J. (2023). Ontology of 3D virtual modeling in digital twin: a review, analysis and thinking. Journal of Intelligent Manufacturing. doi:10.1007/s10845-023-02246-6
Deep Learning - Powered Radio Frequency Fingerprint Identification: Methodology and Case Study
Shen, G., Zhang, J., & Marshall, A. (2023). Deep Learning - Powered Radio Frequency Fingerprint Identification: Methodology and Case Study. IEEE Communications Magazine, 61(9), 170-176. doi:10.1109/mcom.001.2200695
Radio Frequency Fingerprint Identification for Device Authentication in the Internet of Things
Zhang, J., Shen, G., Saad, W., & Chowdhury, K. (2023). Radio Frequency Fingerprint Identification for Device Authentication in the Internet of Things. IEEE Communications Magazine. doi:10.1109/MCOM.003.2200974
Design of a Channel Robust Radio Frequency Fingerprint Identification Scheme
Xing, Y., Hu, A., Zhang, J., Peng, L., & Wang, X. (2023). Design of a Channel Robust Radio Frequency Fingerprint Identification Scheme. IEEE INTERNET OF THINGS JOURNAL, 10(8), 6946-6959. doi:10.1109/JIOT.2022.3228280
H2K: A Heartbeat-Based Key Generation Framework for ECG and PPG Signals
Zhang, J., Zheng, Y., Xu, W., & Chen, Y. (2023). H2K: A Heartbeat-Based Key Generation Framework for ECG and PPG Signals. IEEE TRANSACTIONS ON MOBILE COMPUTING, 22(2), 923-934. doi:10.1109/TMC.2021.3096384
Authorized and Rogue LTE Terminal Identification Using Wavelet Coefficient Graph with Auto-encoder
Wu, Z., Peng, L., Zhang, J., Liu, M., Fu, H., & Hu, A. (2023). Authorized and Rogue LTE Terminal Identification Using Wavelet Coefficient Graph with Auto-encoder. In 2022 IEEE 96TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-FALL). doi:10.1109/VTC2022-Fall57202.2022.10012861
Signal-independent RFF Identification for LTE Mobile Devices via Ensemble Deep Learning
Qiu, Y., Peng, L., Zhang, J., Liu, M., Fu, H., & Hu, A. (2023). Signal-independent RFF Identification for LTE Mobile Devices via Ensemble Deep Learning. In 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022) (pp. 37-42). doi:10.1109/GLOBECOM48099.2022.10000722
A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices
Xing, Y., Chen, X., Zhang, J., Hu, A., & Zhang, D. (2023). A Noise-Robust Radio Frequency Fingerprint Identification Scheme for Internet of Things Devices. In IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 1-6). IEEE. doi:10.1109/infocomwkshps57453.2023.10225749
Deep Learning-Enhanced Physical Layer Authentication for Mobile Devices
Guo, Y., Zhang, J., & Hong, Y. -W. P. (2023). Deep Learning-Enhanced Physical Layer Authentication for Mobile Devices. In GLOBECOM 2023 - 2023 IEEE Global Communications Conference (pp. 826-831). IEEE. doi:10.1109/globecom54140.2023.10437299
Federated Radio Frequency Fingerprinting with Model Transfer and Adaptation
Zhang, C., Dang, S., Zhang, J., Zhang, H., & Beach, M. A. (2023). Federated Radio Frequency Fingerprinting with Model Transfer and Adaptation. In IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 1-6). IEEE. doi:10.1109/infocomwkshps57453.2023.10226112
Joint Precoding and Phase Shift Design in Reconfigurable Intelligent Surfaces-Assisted Secret Key Generation
Lu, T., Chen, L., Zhang, J., Chen, C., & Hu, A. (2023). Joint Precoding and Phase Shift Design in Reconfigurable Intelligent Surfaces-Assisted Secret Key Generation. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 18, 3251-3266. doi:10.1109/TIFS.2023.3268881
Machine Learning-Based Secret Key Generation for IRS-Assisted Multi-Antenna Systems
Chen, C., Zhang, J., Lu, T., Sandell, M., & Chen, L. (2023). Machine Learning-Based Secret Key Generation for IRS-Assisted Multi-Antenna Systems. In ICC 2023 - IEEE International Conference on Communications (pp. 5861-5866). IEEE. doi:10.1109/icc45041.2023.10279041
Precoding Design for Key Generation in Near-Field Extremely Large-Scale MIMO Communications
Lu, T., Chen, L., Zhang, J., Chen, C., Duong, T. Q., & Matthaiou, M. (2023). Precoding Design for Key Generation in Near-Field Extremely Large-Scale MIMO Communications. In 2023 IEEE Globecom Workshops (GC Wkshps) (pp. 172-177). IEEE. doi:10.1109/gcwkshps58843.2023.10464921
Reconfigurable Intelligent Surface-Assisted Key Generation for Millimeter Wave Communications
Lu, T., Chen, L., Zhang, J., Chen, C., & Duong, T. Q. (2023). Reconfigurable Intelligent Surface-Assisted Key Generation for Millimeter Wave Communications. In 2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC. doi:10.1109/WCNC55385.2023.10119128
RelativeRFF: Multi-Antenna Device Identification in Multipath Propagation Scenarios
Luo, H., Li, G., Xing, Y., Zhang, J., Hu, A., & Wang, X. (2023). RelativeRFF: Multi-Antenna Device Identification in Multipath Propagation Scenarios. In ICC 2023 - IEEE International Conference on Communications (pp. 3708-3713). IEEE. doi:10.1109/icc45041.2023.10279540
Toward Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification
Shen, G., Zhang, J., Marshall, A., Valkama, M., & Cavallaro, J. R. (2023). Toward Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 18, 2355-2367. doi:10.1109/TIFS.2023.3266626
White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification
Ma, J., Zhang, J., Shen, G., Marshall, A., & Chang, C. -H. (2023). White-Box Adversarial Attacks on Deep Learning-Based Radio Frequency Fingerprint Identification. In ICC 2023 - IEEE International Conference on Communications (pp. 3714-3719). IEEE. doi:10.1109/icc45041.2023.10278927
2022
Radio Frequency Fingerprinting Exploiting Non-Linear Memory Effect
Li, Y., Ding, Y., Zhang, J., Goussetis, G., & Podilchak, S. K. K. (2022). Radio Frequency Fingerprinting Exploiting Non-Linear Memory Effect. IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 8(4), 1618-1631. doi:10.1109/TCCN.2022.3212414
Radio Frequency Fingerprints vs. Physical Unclonable Functions-Are They Twins, Competitors, or Allies?
Zhang, J., Chang, C. -H., Gu, C., & Hanzo, L. (2022). Radio Frequency Fingerprints vs. Physical Unclonable Functions-Are They Twins, Competitors, or Allies?. IEEE NETWORK, 36(6), 68-75. doi:10.1109/MNET.107.2100372
Physical-Layer-Based Secure Communications for Static and Low-Latency Industrial Internet of Things
Ji, Z., Yeoh, P. L., Chen, G., Zhang, J., Zhang, Y., He, Z., . . . Li, Y. (2022). Physical-Layer-Based Secure Communications for Static and Low-Latency Industrial Internet of Things. IEEE INTERNET OF THINGS JOURNAL, 9(19), 18392-18405. doi:10.1109/JIOT.2022.3160508
A channel perceiving attack and the countermeasure on long-range IoT physical layer key generation
Yang, L., Gao, Y., Zhang, J., Camtepe, S., & Jayalath, D. (2022). A channel perceiving attack and the countermeasure on long-range IoT physical layer key generation. COMPUTER COMMUNICATIONS, 191, 108-118. doi:10.1016/j.comcom.2022.04.027
LoRaWAN Physical Layer-Based Attacks and Countermeasures, A Review
Ruotsalainen, H., Shen, G., Zhang, J., & Fujdiak, R. (2022). LoRaWAN Physical Layer-Based Attacks and Countermeasures, A Review. SENSORS, 22(9). doi:10.3390/s22093127
Deep-Learning-Based Physical-Layer Secret Key Generation for FDD Systems
Zhang, X., Li, G., Zhang, J., Hu, A., Hou, Z., & Xiao, B. (2022). Deep-Learning-Based Physical-Layer Secret Key Generation for FDD Systems. IEEE INTERNET OF THINGS JOURNAL, 9(8), 6081-6094. doi:10.1109/JIOT.2021.3109272
Reconfigurable Intelligent Surface Assisted Secret Key Generation in Quasi-Static Environments
Lu, T., Chen, L., Zhang, J., Cao, K., & Hu, A. (2022). Reconfigurable Intelligent Surface Assisted Secret Key Generation in Quasi-Static Environments. IEEE COMMUNICATIONS LETTERS, 26(2), 244-248. doi:10.1109/LCOMM.2021.3130635
Colluding RF Fingerprint Impersonation Attack Based on Generative Adversarial Network
Xu, Y., Liu, M., Peng, L., Zhang, J., & Zheng, Y. (2022). Colluding RF Fingerprint Impersonation Attack Based on Generative Adversarial Network. In IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022) (pp. 3220-3225). doi:10.1109/ICC45855.2022.9838574
Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa
Shen, G., Zhang, J., Marshall, A., & Cavallaro, J. (n.d.). Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa. IEEE Transactions on Information Forensics and Security. Retrieved from http://arxiv.org/abs/2107.02867v1
2021
Radio Frequency Fingerprint Identification for LoRa Using Deep Learning
Shen, G., Zhang, J., Marshall, A., Peng, L., & Wang, X. (2021). Radio Frequency Fingerprint Identification for LoRa Using Deep Learning. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 39(8), 2604-2616. doi:10.1109/JSAC.2021.3087250
Radio Frequency Fingerprint Identification for LoRa Using Spectrogram and CNN
Shen, G., Zhang, J., Marshall, A., Peng, L., & Wang, X. (2021). Radio Frequency Fingerprint Identification for LoRa Using Spectrogram and CNN. In IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2021). doi:10.1109/INFOCOM42981.2021.9488793
NISA: Node Identification and Spoofing Attack Detection Based on Clock Features and Radio Information for Wireless Sensor Networks
Huan, X., Kim, K. S., & Zhang, J. (2021). NISA: Node Identification and Spoofing Attack Detection Based on Clock Features and Radio Information for Wireless Sensor Networks. IEEE Transactions on Communications, 1. doi:10.1109/tcomm.2021.3071448
Key Generation for Internet of Things
Xu, W., Zhang, J., Huang, S., Luo, C., & Li, W. (2021). Key Generation for Internet of Things. ACM Computing Surveys, 54(1).
Encrypting Wireless Communications on the Fly Using One-Time Pad and Key Generation
Li, G., Zhang, Z., Zhang, J., & Hu, A. (2021). Encrypting Wireless Communications on the Fly Using One-Time Pad and Key Generation. IEEE INTERNET OF THINGS JOURNAL, 8(1), 357-369. doi:10.1109/JIOT.2020.3004451
LTE Device Identification Based on RF Fingerprint with Multi-Channel Convolutional Neural Network
Yin, P., Peng, L., Zhang, J., Liu, M., Fu, H., & Hu, A. (2021). LTE Device Identification Based on RF Fingerprint with Multi-Channel Convolutional Neural Network. In 2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM). doi:10.1109/GLOBECOM46510.2021.9685067
Radio Frequency Fingerprint Identification for Narrowband Systems, Modelling and Classification
Zhang, J., Woods, R., Sandell, M., Valkama, M., Marshall, A., & Cavallaro, J. (2021). Radio Frequency Fingerprint Identification for Narrowband Systems, Modelling and Classification. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 16, 3974-3987. doi:10.1109/TIFS.2021.3088008
Radio Frequency Fingerprint Identification for Security in Low-Cost IoT Devices
Shen, G., Zhang, J., Marshall, A., Valkama, M., & Cavallaro, J. (2021). Radio Frequency Fingerprint Identification for Security in Low-Cost IoT Devices. Retrieved from http://arxiv.org/abs/2111.14275v1
Sum Secret Key Rate Maximization for TDD Multi-User Massive MIMO Wireless Networks
Li, G., Sun, C., Jorswieck, E. A., Zhang, J., Hu, A., & Chen, Y. (2021). Sum Secret Key Rate Maximization for TDD Multi-User Massive MIMO Wireless Networks. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 16, 968-982. doi:10.1109/TIFS.2020.3026466
2020
Design of a Robust Radio-Frequency Fingerprint Identification Scheme for Multimode LFM Radar
Xing, Y., Hu, A., Zhang, J., Yu, J., Li, G., & Wang, T. (2020). Design of a Robust Radio-Frequency Fingerprint Identification Scheme for Multimode LFM Radar. IEEE INTERNET OF THINGS JOURNAL, 7(10), 10581-10593. doi:10.1109/JIOT.2020.3003692
Key Generation for Internet of Things: A Contemporary Survey
Xu, W., Zhang, J., Huang, S., Luo, C., & Li, W. (n.d.). Key Generation for Internet of Things: A Contemporary Survey. ACM Computing Surveys. Retrieved from http://arxiv.org/abs/2007.15956v2
A New Frontier for IoT Security Emerging From Three Decades of Key Generation Relying on Wireless Channels
Zhang, J., Li, G., Marshall, A., Hu, A., & Hanzo, L. (2020). A New Frontier for IoT Security Emerging From Three Decades of Key Generation Relying on Wireless Channels. IEEE Access, 8, 138406-138446. doi:10.1109/ACCESS.2020.3012006
Beam-Domain Secret Key Generation for Multi-User Massive MIMO Networks
Chen, Y., Li, G., Sun, C., Zhang, J., Jorswieck, E., & Xiao, B. (2020). Beam-Domain Secret Key Generation for Multi-User Massive MIMO Networks. In ICC 2020 - 2020 IEEE International Conference on Communications (ICC) (pp. 1-6). Dublin, Ireland: IEEE. doi:10.1109/icc40277.2020.9149130
Experimental Investigation on Wireless Key Generation for Low-Power Wide-Area Networks
Ruotsalainen, H., Zhang, J., & Grebeniuk, S. (2020). Experimental Investigation on Wireless Key Generation for Low-Power Wide-Area Networks. IEEE INTERNET OF THINGS JOURNAL, 7(3), 1745-1755. doi:10.1109/JIOT.2019.2946919
Deep Learning Based RF Fingerprint Identification Using Differential Constellation Trace Figure
Peng, L., Zhang, J., Liu, M., & Hu, A. (2020). Deep Learning Based RF Fingerprint Identification Using Differential Constellation Trace Figure. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 69(1), 1091-1095. doi:10.1109/TVT.2019.2950670
2019
Physical Layer Security for the Internet of Things: Authentication and Key Generation
Zhang, J., Rajendran, S., Sun, Z., Woods, R., & Hanzo, L. (2019). Physical Layer Security for the Internet of Things: Authentication and Key Generation. IEEE WIRELESS COMMUNICATIONS, 26(5), 92-98. doi:10.1109/MWC.2019.1800455
Design of an Efficient OFDMA-Based Multi-User Key Generation Protocol
Zhang, J., Ding, M., Lopez-Perez, D., Marshall, A., & Hanzo, L. (2019). Design of an Efficient OFDMA-Based Multi-User Key Generation Protocol. IEEE Transactions on Vehicular Technology, 68(9), 8842-8852. doi:10.1109/TVT.2019.2929362
Key Generation Based on Large Scale Fading
Zhang, J., Ding, M., Li, G., & Marshall, A. (2019). Key Generation Based on Large Scale Fading. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 68(8), 8222-8226. doi:10.1109/TVT.2019.2922443
Time-Modulated OFDM Directional Modulation Transmitters
Ding, Y., Fusco, V., Zhang, J., & Wang, W. -Q. (2019). Time-Modulated OFDM Directional Modulation Transmitters. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 68(8), 8249-8253. doi:10.1109/TVT.2019.2924543
Machine Learning Based Attack Against Artificial Noise-Aided Secure Communication
Wen, Y., Yoshida, M., Zhang, J., Chu, Z., Xiao, P., & Tafazolli, R. (2019). Machine Learning Based Attack Against Artificial Noise-Aided Secure Communication. In ICC 2019 - 2019 IEEE International Conference on Communications (ICC). IEEE. doi:10.1109/icc.2019.8761569
Design of an Energy-Efficient Multidimensional Secure Constellation for 5G Communications
Li, W., Ghogho, M., Zhang, J., McLernon, D., Lei, J., Zaidi, S. A. R., & IEEE. (2019). Design of an Energy-Efficient Multidimensional Secure Constellation for 5G Communications. In 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS). Retrieved from http://gateway.webofknowledge.com/
Physical Layer Key Generation in 5G and Beyond Wireless Communications: Challenges and Opportunities
Li, G., Sun, C., Zhang, J., Jorswieck, E., Xiao, B., & Hu, A. (2019). Physical Layer Key Generation in 5G and Beyond Wireless Communications: Challenges and Opportunities. ENTROPY, 21(5). doi:10.3390/e21050497
An Investigation of Using Loop-Back Mechanism for Channel Reciprocity Enhancement in Secret Key Generation
Peng, L., Li, G., Zhang, J., Woods, R., Liu, M., & Hu, A. (2019). An Investigation of Using Loop-Back Mechanism for Channel Reciprocity Enhancement in Secret Key Generation. IEEE TRANSACTIONS ON MOBILE COMPUTING, 18(3), 507-519. doi:10.1109/TMC.2018.2842215
2018
Channel-Envelope Differencing Eliminates Secret Key Correlation: LoRa-Based Key Generation in Low Power Wide Area Networks
Zhang, J., Marshall, A., & Hanzo, L. (2018). Channel-Envelope Differencing Eliminates Secret Key Correlation: LoRa-Based Key Generation in Low Power Wide Area Networks. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 67(12), 12462-12466. doi:10.1109/TVT.2018.2877201
Constructing Reciprocal Channel Coefficients for Secret Key Generation in FDD Systems
Li, G., Hu, A., Sun, C., & Zhang, J. (2018). Constructing Reciprocal Channel Coefficients for Secret Key Generation in FDD Systems. IEEE COMMUNICATIONS LETTERS, 22(12), 2487-2490. doi:10.1109/LCOMM.2018.2875708
On Radio Frequency Fingerprint Identification for DSSS Systems in Low SNR Scenarios
Xing, Y., Hu, A., Zhang, J., Peng, L., & Li, G. (2018). On Radio Frequency Fingerprint Identification for DSSS Systems in Low SNR Scenarios. IEEE COMMUNICATIONS LETTERS, 22(11), 2326-2329. doi:10.1109/LCOMM.2018.2871454
Securing M2M Transmissions Using Nonreconciled Secret Keys Generated from Wireless Channels
Peng, L., Li, G., Zhang, J., & Hu, A. (2018). Securing M2M Transmissions Using Nonreconciled Secret Keys Generated from Wireless Channels. In 2018 IEEE GLOBECOM WORKSHOPS (GC WKSHPS). Retrieved from https://www.webofscience.com/
High-Agreement Uncorrelated Secret Key Generation Based on Principal Component Analysis Preprocessing
Li, G., Hu, A., Zhang, J., Peng, L., Sun, C., & Cao, D. (2018). High-Agreement Uncorrelated Secret Key Generation Based on Principal Component Analysis Preprocessing. IEEE TRANSACTIONS ON COMMUNICATIONS, 66(7), 3022-3034. doi:10.1109/TCOMM.2018.2814607
Security Optimization of Exposure Region-Based Beamforming With a Uniform Circular Array
Zhang, Y., Woods, R., Ko, Y., Marshall, A., & Zhang, J. (2018). Security Optimization of Exposure Region-Based Beamforming With a Uniform Circular Array. IEEE TRANSACTIONS ON COMMUNICATIONS, 66(6), 2630-2641. doi:10.1109/TCOMM.2017.2768516
Design of a Hybrid RF Fingerprint Extraction and Device Classification Scheme
Peng, L., Hu, A., Zhang, J., Jiang, Y., Yu, J., & Yan, Y. (2018). Design of a Hybrid RF Fingerprint Extraction and Device Classification Scheme. IEEE Internet of Things Journal, 6(1), 349-360. doi:10.1109/JIOT.2018.2838071
Distributed OFDM transmitter scheme for internet of things
Ding, Y., Fusco, V., & Zhang, J. (2018). Distributed OFDM transmitter scheme for internet of things. In Iet Conference Publications Vol. 2018.
2017
Securing Wireless Communications of the Internet of Things from the Physical Layer, An Overview
Zhang, J., Duong, T. Q., Woods, R., & Marshall, A. (2017). Securing Wireless Communications of the Internet of Things from the Physical Layer, An Overview. ENTROPY, 19(8). doi:10.3390/e19080420
Secure Cooperative Single Carrier Systems Under Unreliable Backhaul and Dense Networks Impact
Nguyen, H. T., Zhang, J., Yang, N., Duong, T. Q., & Hwang, W. -J. (2017). Secure Cooperative Single Carrier Systems Under Unreliable Backhaul and Dense Networks Impact. IEEE ACCESS, 5, 18310-18324. doi:10.1109/ACCESS.2017.2727399
Phase Error Effects on Distributed Transmit Beamforming for Wireless Communications
Ding, Y., Fusco, V., & Zhang, J. (2017). Phase Error Effects on Distributed Transmit Beamforming for Wireless Communications. In 2017 11TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP). Retrieved from https://www.webofscience.com/
On the Key Generation From Correlated Wireless Channels
Zhang, J., He, B., Duong, T. Q., & Woods, R. (2017). On the Key Generation From Correlated Wireless Channels. IEEE COMMUNICATIONS LETTERS, 21(4), 961-964. doi:10.1109/LCOMM.2017.2649496
Design of OFDM Physical Layer Encryption Scheme
Zhang, J., Marshall, A. J., Woods, R., & Duong, T. Q. (2017). Design of OFDM Physical Layer Encryption Scheme. IEEE Transactions on Vehicular Technology, 66(3), 2114-2127. doi:10.1109/TVT.2016.2571264
Key generation from wireless channels: a survey and practical implementation
Zhang, J., Duong, T. Q., Woods, R., & Marshall, A. (2017). Key generation from wireless channels: a survey and practical implementation. In TRUSTED COMMUNICATIONS WITH PHYSICAL LAYER SECURITY FOR 5G AND BEYOND (Vol. 76, pp. 457-474). Retrieved from https://www.webofscience.com/
Retrodirective-Assisted Secure Wireless Key Establishment
Ding, Y., Zhang, J., & Fusco, V. F. (2017). Retrodirective-Assisted Secure Wireless Key Establishment. IEEE TRANSACTIONS ON COMMUNICATIONS, 65(1), 320-334. doi:10.1109/TCOMM.2016.2616406
Security Analysis of a Novel Artificial Randomness Approach for Fast Key Generation
Li, G., Hu, A., Zhang, J., & Xiao, B. (2017). Security Analysis of a Novel Artificial Randomness Approach for Fast Key Generation. In GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE. Retrieved from https://www.webofscience.com/
2016
Green two-tiered wireless multimedia sensor systems: an energy, bandwidth, and quality optimisation framework
Nguyen-Son, V., Dac-Binh, H., Canberk, B., & Zhang, J. (2016). Green two-tiered wireless multimedia sensor systems: an energy, bandwidth, and quality optimisation framework. IET COMMUNICATIONS, 10(18), 2543-2550. doi:10.1049/iet-com.2016.0406
Impact of primary networks on the performance of energy harvesting cognitive radio networks
Zhang, J., Nam-Phong, N., Zhang, J., Garcia-Palacios, E., & Ngoc, P. L. (2016). Impact of primary networks on the performance of energy harvesting cognitive radio networks. IET COMMUNICATIONS, 10(18), 2559-2566. doi:10.1049/iet-com.2016.0400
Experimental Study on Key Generation for Physical Layer Security in Wireless Communications
Zhang, J., Woods, R., Duong, T. Q., Marshal, A., Ding, Y., Huang, Y., & Xu, Q. (2016). Experimental Study on Key Generation for Physical Layer Security in Wireless Communications. IEEE Access, 4, 4464-4477. doi:10.1109/ACCESS.2016.2604618
Experimental Study on Channel Reciprocity in Wireless Key Generation
Zhang, J., Woods, R., Duong, T. Q., Marshall, A., & Ding, Y. (2016). Experimental Study on Channel Reciprocity in Wireless Key Generation. In 2016 IEEE 17TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC). doi:10.1109/SPAWC.2016.7536825
Efficient Key Generation by Exploiting Randomness From Channel Responses of Individual OFDM Subcarriers
Zhang, J., Marshall, A., Woods, R., & Duong, T. Q. (2016). Efficient Key Generation by Exploiting Randomness from Channel Responses of Individual OFDM Subcarriers. IEEE Transitions on Communications, 64(6), 2578-2588. doi:10.1109/TCOMM.2016.2552165
Key Generation From Wireless Channels: A Review
Zhang, J., Duong, T. Q., Marshall, A., & Woods, R. (2016). Key Generation From Wireless Channels: A Review. IEEE ACCESS, 4, 614-626. doi:10.1109/ACCESS.2016.2521718
Secure Wireless Key Establishment Using Retrodirective Array
Ding, Y., Zhang, J., & Fusco, V. (2016). Secure Wireless Key Establishment Using Retrodirective Array. In 2016 IEEE GLOBECOM WORKSHOPS (GC WKSHPS). Retrieved from https://www.webofscience.com/
2015
AN EFFECTIVE KEY GENERATION SYSTEM USING IMPROVED CHANNEL RECIPROCITY
Zhang, J., Woods, R., Marshall, A., Duong, T. Q., & IEEE. (2015). AN EFFECTIVE KEY GENERATION SYSTEM USING IMPROVED CHANNEL RECIPROCITY. In 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) (pp. 1727-1731). Retrieved from http://gateway.webofknowledge.com/
Frequency diverse array OFDM transmitter for secure wireless communication
Ding, Y., Zhang, J., & Fusco, V. (2015). Frequency diverse array OFDM transmitter for secure wireless communication. ELECTRONICS LETTERS, 51(17), 1374-1375. doi:10.1049/el.2015.1491
AN EFFECTIVE KEY GENERATION SYSTEM USING IMPROVED CHANNEL RECIPROCITY
Zhang, J., Woods, R., Marshall, A., & Duong, T. Q. (2015). AN EFFECTIVE KEY GENERATION SYSTEM USING IMPROVED CHANNEL RECIPROCITY. In 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) (pp. 1727-1731). Retrieved from https://www.webofscience.com/
Verification of Key Generation from Individual OFDM Subcarrier's Channel Response
Zhang, J., Woods, R., Marshall, A., & Duong, T. Q. (2015). Verification of Key Generation from Individual OFDM Subcarrier's Channel Response. In 2015 IEEE GLOBECOM WORKSHOPS (GC WKSHPS). Retrieved from https://www.webofscience.com/
2014
Secure Key Generation from OFDM Subcarriers' Channel Responses
Zhang, J., Marshall, A., Woods, R., & Duong, T. Q. (2014). Secure Key Generation from OFDM Subcarriers' Channel Responses. In 2014 GLOBECOM WORKSHOPS (GC WKSHPS) (pp. 1302-1307). Retrieved from https://www.webofscience.com/