Jingjie Li

Current Institution: University of Wisconsin-Madison

Email: jingjie.li@wisc.edu

Bio: Jingjie Li is a Ph.D. candidate in computer engineering at the University of Wisconsin—Madison. Jingjie obtained his BEng (R&D) degree with first-class honours from the Australian National University in 2017. Now he works with Prof. Younghyun Kim and Prof. Kassem Fawaz on human-centered computing and usable security and privacy (S&P). Jingjie designs usable and privacy-aware interfaces for smart device users. He published his work at top S&P conferences, e.g. USENIX Security and ACM CCS, focusing on the privacy of biometrics. Jingjie is also interested in designing interactive and power-efficient systems, contributing to multiple publications in broader fields and venues, including ACM CHI, ISCA, and ISLPED. Jingjie received several academic awards and recognitions, including IEEE Micro Top Picks, ACM CHI Best Paper Award, ISLPED Low-Power Design Contest Award, and A. Richard Newton Young Student Fellowship. For more information, please visit https://jingjieli95.github.io/.

Abstract: Usable Privacy for Biometrics-Based Authentication on Smart Devices

Smart devices, such as wearables, smart appliances, and mixed reality headsets, are blurring the boundaries between the physical and digital domains. The great advancements, however, come with considerable security and privacy challenges. In exchange for usability of using biometrics as a unique token or input modality in diverse usage contexts, users often pay the price in privacy via revealing biometric data in authentication. This privacy-usability tradeoff is opaque to users from system implementation to privacy implications, especially for emerging biometrics, e.g., eye movement. This privacy concern motivates my research: how to design privacy-preserving systems for usable biometrics-based authentication? My research aims to bridge the gaps in the complicated tradeoffs of designing biometrics-based user authentication to preserve both privacy and usability through three research thrusts, which are i) privacy for biometrics template, ii) infrastructure support for privacy control, iii) accessible interface for privacy communication.