报告题目：Privacy Leakage and Leaking Device Identification in Wi-Fi-integrated IoT Environments
报 告 人：Zakirul Alam Bhuiyan
报告时间：2023年11月25日 9:30
报告地点：临江楼A103会议室
主 持 人：刘琦教授、许小龙教授
报告人简介：
Zakirul Alam Bhuiyan, PhD, is an Associate Professor in Cybersecurity at the Department of Computer and Information Sciences at Fordham University, NY, USA. He is the Director of the Dependable and Secure System Research (DependSys) Lab and is affiliated with the Fordham Center for Cybersecurity. His research focuses on data-driven dependability, cybersecurity and privacy, trustworthy AI/ML, and emerging IoT/CPS applications. Dr. Bhuiyan authored/co-authored over 250 publications that appeared in many prestigious journals. He has been identified as the High-Cited Researcher (2020-2022) and ranked as the “World’s Rising Stars of Science” (2022). He has served as an organizer, general chair, program chair, workshop chair, and TPC member of various international conferences, including IEEE INFOCOM. He is a Senior Member of IEEE and a member of ACM.
报告简介：
Nowadays, wireless signals, such as Wi-Fi signals, are omnipresent and around us; some pass through us, and some reflect off us. Recent advancement shows that these signals can be leveraged and applied to many promising applications, including healthcare and activity monitoring, motion detection, gesture recognition, etc. Besides, cyber attackers may get motivated by this advancement that Wi-Fi signals can be leveraged for evil intentions, such as monitoring. More importantly, unauthorized devices (such as sniffers) can be deployed, or some existing Wi-Fi devices can be compromised to monitor a Wi-Fi-integrated environment remotely by cyber attackers. As a result, there can be significant privacy leakage that is usually undiscovered and unrealized. The same device signals can be forwarded to the remote attackers, and attackers can utilize them to learn the target activities in an unauthorized and unauthenticated manner. The devices that leak privacy remain undiscovered and need to be identified. In this talk, I will discuss this together with the two aspects: privacy leakage and leaking device identification. I will show what our environment looks like, how unauthorized IoT devices can be employed, how such devices can be used to observe privacy, and how received signals can be utilized to leak privacy, and more. Finally, I'll talk about future work.
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