Dr. Qiaosheng Zhang, a young researcher of Shanghai Artificial Intelligence Laboratory, was invited to deliver an online academic report with the theme of "Covert Communication: From Information-theoretic Limits to Code Designs" in the morning of November 4th, 2022. The report was hosted by Ms. Zhou Lin from the School of Cyber Science and Technology of Beihang University. More than 50 professors and students participated online.
In his report, Dr. Zhang first introduced the background of covert communication in information theory, and then introduced Bash, Wang, Bolch et al. 's classical results on covert capacity in binary discrete memory-free channel (DMC) and Gaussian channel (AWGN). Then the paper introduces and analyzes the three covert measures of Detection error probability, Variational distance and KL-divergence in covert communication, and gave out the conditions to be met by covert communication code words. In addition, Dr. Zhang introduced the code reachability analysis of IID codebook, PPM codebook, Gaussian codebook and BPSK codebook, and gave the conditions of whether secret key sharing is needed to ensure the concealment in covert communication. Next, Dr. Zhang introduced his own research achievements in the field of covert communication, including: polynomial time encoding strategy in binary discrete memory-free channels, covert communication in the scenario of mismatch decoder, covert communication in the presence of active attack behavior of eavesdropper, and authentication in covert communication.
At the end of the lecture, Dr. Zhang answered the questions raised by the teachers and students present, and had an in-depth exchange and discussion with the teachers and students present on the details of coding strategy, covert measurement and channel model in covert communication.
【 Brief Introduction of the speaker 】
Dr.Zhang received his Bachelor's degree and PhD degree from the Department of Information Engineering of the Chinese University of Hong Kong in 2015 and 2019 under the guidance of Sidharth Jaggi and Mayank Bakshi. Research fellow at the National University of Singapore (with Vincent Y. F. Tan) and Huawei Hong Kong Institute from 2019 to 2022; He joined the Shanghai AI Laboratory as a young researcher in 2022. His research interests include information theory, covert communication, statistical learning, reinforcement learning, etc.
