演講題目：On Physical-Layer Authentication via Online Transfer Learning

演  講  者：Prof. Shih Yu Chang, San Jose State University, San Jose, CA, USA

時　　間：2022/12/21, Wednesday 13:00~15:00

地　　點：清華大學台達館304室 (Delta Building R304)

ABSTRACT

This work introduces a novel physical layer (PHYlayer) authentication scheme, called Transfer Learning based PHY-layer Authentication (TL-PHA), aiming to achieve fast online user authentication that is highly desired for latency sensitive applications such as edge computing. The proposed TL-PHA scheme is characterized by incorporating with a novel convolutional neural network architecture, namely Triple Pool Network (TP-Net), for achieving lightweight and online classification, as well as effective data augmentation methods for generation of dataset samples for the network model training. To assess the performance of the proposed scheme, we conducted two sets of experiments, including the one using computer simulated channel data, and the other utilizing real experiment data generated by our wireless testbed. The results demonstrate the superiority of the proposed scheme in terms of authentication accuracy, detection rate, and training complexity compared with all the considered counterparts.

After this work technical discussion, we will also provide discussions about future works about applying data/science to IoT.

BIOGRAPHY

Shih Yu Chang received a B. S. E. E. degree from National Taiwan University, Taiwan, in 1998, and Ph. D. degrees in electrical engineering and computer engineering from University of Michigan, Ann Arbor, in 2006. From August 2006 to February 2016, he was the faculty in the Department of Computer Engineering, National Tsing Hua University, Hsinchu, Taiwan. From July to August 2007, Dr. Chang had been a visiting assistant professor at Television and Networks Transmission Group, Communications Research Center, Ottawa, Canada. From June 2018, he began to provide lectures about machine learning, data science, and AI in San Jose State University, San Jose, CA, USA. Besides academic positions, Dr. Chang also works as an AI technical lead focusing on applying machine learning techniques to automate office work.

Dr. Chang has published more than 80 peer-refereed technical journals and conference articles in electrical and computer engineering. His research interests include the areas of wireless networks, wireless communications and signal processing. He currently serves as the technical committee, symposium chair, track chair, or the reviewer in networking, signal processing, communications, and computers.