Artwork

Content provided by Sanoop Thomas. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sanoop Thomas or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Player FM - Podcast App
Go offline with the Player FM app!

SecTools Podcast E21 With Emily Wenger

27:24
 
Share
 

Manage episode 303108614 series 2986552
Content provided by Sanoop Thomas. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sanoop Thomas or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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

  continue reading

55 episodes

Artwork
iconShare
 
Manage episode 303108614 series 2986552
Content provided by Sanoop Thomas. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Sanoop Thomas or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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

  continue reading

55 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Quick Reference Guide