NAME：Helen, He FANG

He FANG is a Full professor at Soochow University, China. She received Ph.D. degree in Electrical and Computer Engineering from Western University, Canada. Previously, she also received another Ph.D. degree in applied mathematics from Fujian Normal University, Fuzhou, China.

Her research interests include intelligent security and trust provision for Internet of Things (IoT) networks, as well as IoT data analytics and applications. She has published 40 publications, and most of them are IEEE journal papers, including one Invited Paper “Learning-aided physical layer authentication as an intelligent process” in IEEE Transactions on Communications. 

She is the Topical Advisory Panel Members and Guest Editor of Sensors, and Guest Editor of IEEE Wireless Communications, IEEE IoT Magazine, and Processes. During 2019-2021, she served as the Vice-Chair of the Communication/Broadcast Chapter in IEEE London Section, and organized more than 20 IEEE events, which attracted more than 2000 attendees. Moreover, she has given several talks in the area of secure communications. She also served as an IEEE GLOBECOM TPC member, an IEEE VTC TPC member, and serves as an active reviewer for many IEEE journals and conferences, such as IEEE Transactions on Wireless Communications, IEEE Transactions on Communications, and IEEE Wireless Communications.

[1] H. Fang, X. Wang, and L. Hanzo, “Learning-aided physical layer authentication as an intelligent process,” IEEE Transactions on Communications, vol. 67, no. 3, (2019): 2260-2273. (Invited paper, IF: 5.69) 

[2] H. Fang, X. Wang, and L. Hanzo, “Adaptive trust management for soft authentication and progressive authorization relying on physical layer attributes,” IEEE Transactions on Communications, vol. 68, no. 4, (2020): 2607-2620. (IF: 5.69) 

[3] H. Fang, X. Wang, N. Zhao, and N. Al-Dhahir, “Lightweight continuous authentication via intelligently arranged pseudo-random access in 5G-and-beyond,” IEEE Transactions on Communications, vol. 69, no. 6, (2021): 4011-4023. (IF: 5.69) 

[4] H. Fang, X. Wang, and L. Xu, “Fuzzy learning for multi-dimensional adaptive physical layer authentication: a compact and robust approach,” IEEE Transactions on Wireless Communications, vol. 19, no. 8, (2020): 5420-5432. (IF: 6.394) 

[5] H. Fang, L. Xu, and X. Wang, “Coordinated multiple relays based physical layer security improvement: a single leader-multiple followers Stackelberg game scheme,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 1, (2018): 197-209. (IF: 6.211) 

[6] H. Fang, X. Wang, Z. Xiao, and L. Hanzo, “Autonomous collaborative authentication with privacy preservation in 6G: From homogeneity to heterogeneity,” IEEE Network, (2022): To be appear. (IF: 7.503) 

[7] H. Fang, X. Wang, and S. Tomasin, “Machine learning for intelligent authentication in 5G-and-beyond wireless networks,” IEEE Wireless Communications, vol. 26, no. 5, (2019): 55-61. (IF: 11) 

[8] H. Fang, A. Qi, and X. Wang, “Fast authentication and progressive authorization in large-scale IoT: How to leverage AI for security enhancement?” IEEE Network, vol. 34, no. 3, (2020): 24-29. (IF: 7.503) 

[9] Z. Xiao, H. Fang*, and X. Wang, “Distributed nonlinear polynomial graph filter and its output graph spectrum: Filter analysis and design,” IEEE Transactions on Signal Processing, vol. 6, (2021): 1-15. (IF: 5.23)

[10] Z. Xiao, H. Fang*, and X. Wang, “Nonlinear polynomial graph filter for anomalous IoT sensor detection and localization,” IEEE Internet of Things Journal, vol. 7, no. 6, (2020): 4839-4848. (IF: 9.515) 

[11] Z. Xiao, H. Fang*, and X. Wang, “Anomalous IoT sensor data detection: An efficient approach enabled by nonlinear frequency-domain graph analysis,” IEEE Internet of Things Journal, vol. 8, no. 5, (2021): 3812-3821. (IF: 9.515) 

[12] H. Fang, L. Xu, Y. Zou, X. Wang, and K.-K. Raymond Choo, “Three-stage Stackelberg game for defending against full-duplex active eavesdropping attacks in cooperative communication,” IEEE Transactions on Vehicular Technology, vol.67, no.11, (2018): 10788-10799. (IF: 5.339)