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What and Who
Title:A tour of ML security
Speaker:Florian Tramèr
coming from:Stanford University
Speakers Bio:
Event Type:Talk
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Monday, 6 August 2018
Duration:60 Minutes
Building:E9 1
Please note: New Room!
Machine learning (ML) is undergoing rapid development and deployment in an ever-growing list of industries. Every stage of the modern ML pipeline, from crowd-sourced data collection to online prediction interfaces, is accompanied by a plethora of security and privacy challenges.
Florian will give an overview of these challenges, and illustrate some of his recent work that explores attacks and defenses on deployed ML models:
1) How to abuse the rich prediction interfaces of ML models deployed in the cloud to reverse engineer model parameters or training data properties.
2) How to efficiently protect the privacy and integrity of machine learning computations with trusted hardware.
3) What can be done to protect against adversarial examples in realistic threat models (usually not much!), and what this means for recent proposals on "perceptual" ad-blocking.
Name(s):Kathrin Grosse
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:NoTo Location:
Tags, Category, Keywords and additional notes
Attachments, File(s):
Uwe Brahm/MPII/DE, 08/01/2018 12:25 PM
Last modified:
Uwe Brahm/MPII/DE, 08/06/2018 07:01 AM
  • Uwe Brahm, 08/01/2018 12:34 PM
  • Uwe Brahm, 08/01/2018 12:34 PM -- Created document.