ECE SEMINAR: User-Centric Secure and Privacy-Preserving Computing Platforms

Abstract:

Computing is undergoing a significant shift. First, the explosive growth of the Internet of Things (IoT) enables users to interact with computing systems and physical environments in novel ways through perceptual interfaces (e.g., microphones and cameras). Second, machine learning algorithms collect huge amounts of data and make critical decisions on new computing systems. While these trends bring unprecedented functionality, they also drastically increase the number of untrusted algorithms, implementations, interfaces, and the amount of private data processed by them, endangering user security and privacy. To regulate these security and privacy issues, privacy regulations such as GDPR (General Data Protection Regulation), CCPA (California Consumer Privacy Act) went into effect. However, there is a huge gap between the desired high-level security/privacy/ethical properties (from regulations, specifications, users' expectations) and low-level real implementations.

To bridge the gap, my work aims to change how platform architects design secure systems, assist developers by detecting security and privacy violation of implementations and build usable and scalable privacy-preserving systems. In this talk, I will present how my group designs principled solutions to ensure modern and emerging computing platforms' security and privacy. In this talk, I will introduce two developer tools we build to detect security and privacy violations. Using the tools, we found large numbers of policy violations in healthcare voice applications and security property violations in IoT messaging protocol implementations. Additionally, I will discuss our recent work on scalable privacy-preserving machine learning.

Biography:

Yuan Tian is an Assistant Professor of Computer Science at the University of Virginia. Before joining UVA, she obtained her Ph.D. from Carnegie Mellon University in 2017 and interned at Microsoft Research, Facebook, and Samsung Research. Her research interests involve security and privacy and its interactions with computer systems, machine learning, and human-computer interaction. Her current research focuses on developing new computing platforms with strong security and privacy features, particularly in the Internet of Things and mobile systems.

ZOOM LINK: https://duke.zoom.us/j/99106700026?pwd=dmhFUWJndTF3L1BBOVJOUFZiL2JVUT09
PASSCODE: 600951

Event Speaker: 
Yuan Tian
Event Date: 
Thursday, January 27, 2022 - 12:00 to 13:00
Event Recurring: 
Yes
Event Sponsor: 
/principals/users/agrp_PrattSchool_ECE
Event Status: 
Event Location: 
None
Event Contact ID: 
414269
Event Contact: 
Novik, Matthew
Event Contact Email: 
Event Contact Phone: 
919-660-3854
Event Image: 
http://calendar.duke.edu/images/2022/20220127/63e9fa4f520568d6b76637955bbe3737-O-Yuan Tian_20220119022829PM.jpg
Event Sequence: 
0
Event GUID: 
CAL-8a018e8b-7e5b08f6-017e-72bd38d3-00006409demobedework@mysite.edu