[Colloquium] CS Seminar today at 3 pm: Blase Ur, University of Chicago

[Sandra Wallace via Colloquium]

The University of Chicago Computer Science Department

PRESENTS:

“Supporting Security and Privacy Decisions with Data-Driven, User-Centered Methods”

Blase Ur
University of Chicago

Abstract:
I will introduce my research centered on helping users make better security and privacy decisions. I will
first discuss my dissertation work on helping users create better passwords, focusing on two recent
projects. First, we proposed using neural networks to model text passwords' resistance to guessing
attacks and explored how different architectures and training methods impact guessing effectiveness. We
showed that neural networks can often guess passwords more effectively than state-of-the-art
approaches, and that this method can be used for fast and accurate password-strength estimation entirely
client-side. We then developed a password meter that gives users data-driven, actionable feedback on
their password. We found that such a meter leads users to create significantly more secure passwords
without significantly impacting memorability.

I will then introduce a number of projects I am currently starting at UChicago. I am actively seeking
students and collaborators! These projects range from data-driven methods to help users protect their
online privacy, supporting user-centered and retrospective security practices for data in the cloud, and
improving human-computer interaction for both the Internet of Things and machine learning.

Current students (undergraduate and graduate) with potential interests in security, privacy, or human-computer
interaction are highly encouraged to attend. If you are interested in my work, yet unable to
attend the talk, please feel free to reach out: blase at uchicago.edu <mailto:blase at uchicago.edu>

Bio:
Blase Ur is Neubauer Family Assistant Professor of Computer Science at the University of Chicago, where he researches
security, privacy, and human-computer interaction. His work encompasses helping users create strong passwords,
supporting privacy decisions with data, and improving the Internet of Things. He received best paper awards at USENIX
Security 2016 and UbiComp 2014, as well as honorable mentions at CHI 2016 and CHI 2012. His research has been
covered in the NY Times, Forbes, and Ars Technica. He received the 2016 John Karat Usable Privacy and Security
Student Research Award, an NDSEG fellowship, a Fulbright scholarship, and a Yahoo Key Scientific Challenges Award.
He earned his PhD from Carnegie Mellon University under Lorrie Cranor's mentorship and an AB in computer science
from Harvard University.


Thursday, January 19, 2017
3:00 pm
Ryerson 251

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