一、主 题：Electricity Theft Detection via Modeling Attackers’ Behaviors
二、主讲人：美国阿拉巴马州立大学 肖杨 教授
四、参会方式：腾讯会议 会议ID：577 934 876
Smart meters may potentially be attacked or compromised to cause certain security risks including losing tongs of money each year due to thefts. It is challenging to identify malicious meters when there are a large number of users. In this talk, three detection methods are introduced: approximation-based approaches including NFD for electricity theft detection, FNFD for fast electricity theft detection and verification, and CNFD for colluded electricity theft detection. In our methods, we model attackers’ behaviors mathematically and understand attackers thoroughly so that we can detect attackers better.
Dr. Yang Xiao is currently a Full Professor with the Department of Computer Science, The University of Alabama, Tuscaloosa, AL, USA.He is IEEE Fellow and an IET Fellow. His current research interests include cyber-physical systems, the Internet of Things, security, wireless networks, smart grid, and telemedicine. He has published over 300 SCI-indexed journal papers (including over 50 IEEE/ACM transactions papers) and 250 EI indexed refereed conference papers related to these research areas. He was a Voting Member of the IEEE 802.11 Working Group from2001 to 2004, involving the IEEE 802.11 (WIFI) standardization work. He currently serves as the Editor-in-Chief of Cyber-Physical Systems (Journal). He has served an Editorial Board or Associate Editor of 20 international journals, including the IEEE Transactions on Cybernetics since 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014-2015), IEEE Transactions on Vehicular Technology (2007-2009), and IEEE Communications Survey and Tutorials(2007-2014). He has served as a Guest Editor over 20 times of different international journals, including the IEEE Transactions on Network Science and Engineering, IEEE Network, IEEE Wireless Communications, and ACM/Springer Mobile Networks and Applications (MONET).
编辑：林坤 / 审核：林坤 / 发布者：林坤