Our research seeks to empower individuals and organizations to control how their data is used. We use techniques from cryptography, programming languages, machine learning, operating systems, and other areas to both understand and improve the privacy and security of computing as practiced today, and as envisioned in the future. A major current focus is on adversarial machine learning.
SRG Leap Day Lunch (29 February 2024)
We are part of the NSF AI Institute for Agent-based Cyber Threat Intelligence and Operation (ACTION) which seeks to change the way mission-critical systems are protected against sophisticated security threats. Collaboration with UC Santa Barbara (lead), Purdue, UC Berkeley, U Chicago, Georgia Tech, NSU, Rutgers, UIUC, UIC, UW, and WWU.
We are members of the NSF SaTC Frontier Center for Trustworthy Machine Learning (CTML) focused on
developing a rigorous understanding of machine learning vulnerabilities and producing tools, metrics, and methods to mitigate them. Collabortion with the University of Wisconsin (lead), UC Berkeley, UC San Diego, and Stanford.
Active Projects
Inference Privacy
Security ML
Auditing ML Systems