I work in the SAND Lab at the University of Chicago and am advised by Dr. Ben Zhao and Dr. Heather Zheng. I am interested in the intersection of machine learning and privacy. Currently, my research explores the limitations, vulnerabilities, and privacy implications of neural networks.


  • Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models
    Shawn Shan, Emily Wenger (co-first author), Jiayun Zhang, Huiying Li, Haitao Zheng, Ben Y. Zhao
    USENIX Security Symposium (USENIX Security'20), Boston, MA, August 2020
    [Paper] [Website]
  • Gotta Catch 'em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks
    Shawn Shan, Emily Wenger, Bolun Wang, Bo Li, Haitao Zheng, Ben Y. Zhao
    Proceedings of ACM Conference on Computer and Communications Security (CCS). Orlando, FL, November 2020
  • Backdoor Attacks Against Facial Recognition in the Physical World
    Emily Wenger, Josephine Passananti, Yuanshun Yao, Haitao Zheng, Ben Y, Zhao
    In Submission
  • Blacklight: Defending Black-Box Adversarial Attacks on Deep Neural Networks
    Huiying Li, Shawn Shan, Emily Wenger, Jiayun Zhang, Haitao Zheng, Ben Y. Zhao
    In Submission
  • Piracy Resistant Watermarks for Deep Neural Networks
    Huiying Li, Emily Wenger, Ben Y. Zhao, Haitao Zheng
    In Submission