I'm currently a final-year Ph.D student in Department of Computer Science and Technology, Hong Kong University of Science and Technology (HKUST). I work with Prof. Qian Zhang in Huawei-HKUST Invovation Lab.
Before I joined HKUST as a Ph.D student, I received my MPhil degree in Computer Science from Hong Kong University of Science and Technology(HKUST) in June 2013, and B.S degree in Computer Science from South China University of Technology (SCUT) in June 2008.
My research topic is security design for mobile systems. I mainly focus on building security systems/applications for mobile devices by leveraging physical/biological data analysis. I'm also interested in big data analaysis in moible networks, and QoE-based video-streaming optimization.
Secure Pairing through EMG, SenSys'16
Electromyogram (EMG) is the electrical activity caused by human muscle contraction. The random and subtle characteristics of EMG make it an excellent source of secret key. We propose a system that can securely pair wearable devices by exploiting the EMG signal as random source. Extensive evaluation results indicate our system can provide a better security than existing pairing schemes and achieving a competitive secret bit generation rate of 5.51 bit/s while maintaining a success matching rate of 88.84%.
VibID: User Identification through Bio-Vibrometry, IPSN'16
VibID is a novel user identification for wearable devies, which uses a low-cost vibration motor and accelerometer to simulate an unobtrusive vibration to users’ arms and capture corresponding bio-responses. By exploring the body response to vibrations of different frequencies, VibID can distinguish users with an accuracy above 91% and is robust to various confounding factors.
- Lin Yang, Mingxuan Yuan, Yanjiao Chen, Wei Wang, Qian Zhang, Jia Zheng. Personalized User Engagement Modeling for Mobile Videos. Elsevier Computer Networks 2017.
- Wei Wang, Yingjie Chen, Lin Yang, Qian Zhang, Jin Zhang. Detecting On-Body Devices Through Creeping Wave Propagation. IEEE INFOCOM 2017. Acceptance Rate: 20.93% (292 out of 1395)
- Lin Yang, Wei Wang, Qian Zhang. Secret from Muscle: Enabling Secure Pairing with Electromyography. Slides:download. ACM SenSys 2016. Acceptance Rate: 17.65% (21 out of 119)
- Lin Yang, Wei Wang, Qian Zhang. VibID: User Identification through Bio-Vibrometry. Slides: download. ACM/IEEE IPSN 2016. Acceptance Rate: 19.65% (23 out of 117)
- Wei Wang, Lin Yang, Qian Zhang. Touch-And-Guard: Secure Pairing Through Hand Resonance . ACM UbiComp 2016. Acceptance Rate: 17.21% (21 out of 122)
- Lin Yang, Mingxuan Yuan, Wei Wang, Qian Zhang, Jia Zeng. Apps on the Move: A Fine-Grained Analysis of Usage Behavior of Mobile Apps. Slides: download IEEE INFOCOM 2016. Acceptance Rate: 18.25% (300 out of 1644)
- Jiansong Zhang, Jin Zhang, Kun Tan, Lin Yang, Qian Zhang, and Yongguang Zhang. Turning Waste into Wealth: Enabling Communication in Guardband Whitespace. ACM MobiHoc 2015. Acceptance Rate: 14.8% (37 out of 250)
- Lin Yang, Jin Zhang, and Qian Zhang. PESC: A parallel system for clustering ECG streams based on MapReduce. Slides: download. IEEE GlobeCom 2013.