关于召开“Sniffing Visible Light Communication Through Walls”学术报告的通知

2021年05月18日  点击:[]

报告名称:Sniffing Visible Light Communication Through Walls


报告时间:2021/05/19 14:00-15:30

报告形式:腾讯会议,865 261 669

报告摘要:Visible light communication (VLC) is gaining a significant amount of interest as a new paradigm to meet rapidly increasing demands on wireless capacity required by a digitalized world. VLC is considered as a secure wireless communication scheme because VLC signals can be easily constrained within physical boundaries. In this work, for the first time, we show that VLC is not as secure as people thought: VLC can be sniffed through walls! The key principle behind this is that in VLC transmissions, a VLC transmitter not only emits visible light signals but also leaks out "side channel RF signals". The leaked RF signals can be sniffed by a receiver to decode the VLC transmissions even if the receiver is blocked (e.g., by walls) from the VLC transmitter. We design and implement a VLC sniffing system including receiver coil design, signal processing and frame decoding, spanning across hardware and software. Field studies show that with a cheap receiver design, our system can simultaneously sniff transmissions from multiple VLC transmitters 6.4 meters away with a 14 cm concrete wall in between, where the distance exceeds the communication range of most state-of-the-art VLC systems. By simply twining a wired earphone on the arm, we can sniff the VLC transmission 1.9 meters away.

报告人简介:Jie Xiong is currently an Assistant Professor with the College of Information and Computer Sciences, University of Massachusetts Amherst. Jie Xiong received his PhD, MS and BEng degrees from University College London, Duke University and Nanyang Technology University respectively. He was a recipient of the Google European Doctoral Fellowship and the British Computer Society Distinguished Dissertation Award Runner-Up. His current research interests include wireless sensing and mobile computing. His recent work appeared at MobiCom, UbiComp, SenSys, CoNEXT, INFOCOM and NSDI. His work won Best Paper Award at CoNEXT 2014, Best Paper Candidate at SenSys 2019 and Best Paper Honorable Mention Award at MobiCom 2020.


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