Talk by Dr. Haojin Zhu: "Attacks and Defenses of IoT Systems via A Cross-layer Approach"
February 26 (Monday)
National Institute of Informatics
Room 1509, 15th floor
Attacks and Defenses of IoT Systems via A Cross-layer Approach
Haojin Zhu (IEEE M'09-SM'16) received his B.Sc. degree (2002) from Wuhan University (China), his M.Sc.(2005) degree from Shanghai Jiao Tong University (China), both in computer science and the Ph.D. in Electrical and Computer Engineering from the University of Waterloo (Canada), in 2009. Since 2017, he has been a full professor with Computer Science department in Shanghai Jiao Tong University. His current research interests include wireless network security and privacy enhancing technologies. He published 35 international journal papers, including JSAC, TDSC, TPDS, TMC, TWC, TVT, and 60 international conference papers, including ACM CCS, ACM MOBICOM, ACM MOBIHOC, IEEE INFOCOM, IEEE ICDCS.
He received a number of awards including: IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award (2014), Top 100 Most Cited Chinese Papers Published in International Journals (2014), Supervisor of Shanghai Excellent Master Thesis Award (2014), Distinguished Member of the IEEE INFOCOM Technical Program Committee (2015), Outstanding Youth Post Expert Award for Shanghai Jiao Tong University (2014), SMC Young Research Award of Shanghai Jiao Tong University (2011). He was a co-recipient of best paper awards of IEEE ICC (2007) and Chinacom (2008) as well as IEEE GLOBECOM Best Paper Nomination (2014) and WASA Best Paper Runner-Up Award (2017). He received Young Scholar Award of Changjiang Scholar Program by Ministry of Education of P.R. China in 2016.
Along with the high popularity of IoT systems, the security and privacy issues in IoT are receiving an increasing interest. In this study, we present WindTalker, a novel and practical keystroke inference framework that allows an attacker to infer the sensitive keystrokes on a mobile device through WiFi-based side-channel information. WindTalker is motivated from the observation that keystrokes on mobile devices will lead to different hand coverage and the finger motions, which will introduce a unique interference to the multi-path signals and can be reflected by the channel state information (CSI). The adversary can exploit the strong correlation between the CSI fluctuation and the keystrokes to infer the user's number input. WindTalker presents a novel approach to collect the target's CSI data by deploying a public WiFi hotspot. Compared with the previous keystroke inference approach, WindTalker neither deploys external devices close to the target device nor compromises the target device. Instead, it utilizes the public WiFi to collect user's CSI data, which is easy-to-deploy and difficult-to-detect. In addition, it jointly analyzes the traffic and the CSI to launch the keystroke inference only for the sensitive period where password entering occurs. WindTalker can be launched without the requirement of visually seeing the smart phone user's input process, backside motion, or installing any malware on the tablet. We implemented Windtalker on several mobile phones and performed a detailed case study to evaluate the practicality of the password inference towards Alipay, the largest mobile payment platform in the world. The evaluation results show that the attacker can recover the key with a high successful rate.
Our research shows that it needs to jointly consider multiple-layer information (e.g., physical layer, network layer and system layer) to design a secure NCS. It also provides more research opportunities for network security study in a cross-layer fashion.
Yusheng Ji <kei [at] nii.ac.jp>