Emily Wenger is a PhD student at the University of Chicago studying machine learning security and privacy. She’s particularly interested in understanding and preventing the unintended uses/abuses of facial recognition technology.

Emily and team has built Fawkes, a system that helps individuals inoculate their images against unauthorized facial recognition models. Fawkes achieves this by helping users add imperceptible pixel-level changes (we call them "cloaks") to their own photos before releasing them. When used to train facial recognition models, these "cloaked" images produce functional models that consistently cause normal images of the user to be misidentified.


* More about Fawkes http://sandlab.cs.uchicago.edu/fawkes/
* Full Research Paper - http://people.cs.uchicago.edu/~ravenben/publications/pdf/fawkes-usenix20.pdf
* Fawkes - http://sandlab.cs.uchicago.edu/fawkes/
* Source Code - https://github.com/Shawn-Shan/fawkes