Publications
Selected publications
- 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)
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.
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 Vol. 31 (pp. 221-230). IEEE. doi:10.1109/infocom52122.2024.10621289
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.
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
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.
Exploration of Transferable Deep Learning-Aided Radio Frequency Fingerprint Identification Systems
Shen, G., & Zhang, J. (n.d.). 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
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
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
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
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
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
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. IEEE. doi:10.1109/icc45041.2023.10279540
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
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
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
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
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
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
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
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
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
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
2021
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
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
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
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
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
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
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
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
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
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/
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
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/