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Adversarial Vulnerability Bounds for Gaussian Process Classification


Sep 19, 2019
Michael Thomas Smith, Kathrin Grosse, Michael Backes, Mauricio A Alvarez

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* 10 pages + 2 pages references + 7 pages of supplementary. 12 figures. Submitted to AAAI 

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Adversarial Initialization -- when your network performs the way I want


Feb 08, 2019
Kathrin Grosse, Thomas A. Trost, Marius Mosbach, Michael Backes, Dietrich Klakow

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* 16 pages, 20 figures 

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The Limitations of Model Uncertainty in Adversarial Settings


Dec 06, 2018
Kathrin Grosse, David Pfaff, Michael T. Smith, Michael Backes

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* 14 pages, 9 figures, 2 tables 

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MLCapsule: Guarded Offline Deployment of Machine Learning as a Service


Aug 01, 2018
Lucjan Hanzlik, Yang Zhang, Kathrin Grosse, Ahmed Salem, Max Augustin, Michael Backes, Mario Fritz

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Killing Three Birds with one Gaussian Process: Analyzing Attack Vectors on Classification


Jun 06, 2018
Kathrin Grosse, Michael T. Smith, Michael Backes

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* 15 pages, 5 tables, 12 figures 

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How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models


Feb 16, 2018
Kathrin Grosse, David Pfaff, Michael Thomas Smith, Michael Backes

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* 8 pages, 7 pages appendix, 8 figures and 13 tables; improved writing and figures 

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On the (Statistical) Detection of Adversarial Examples


Oct 17, 2017
Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, Patrick McDaniel

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* 13 pages, 4 figures, 5 tables. New version: improved writing, incorporating external feedback 

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Adversarial Perturbations Against Deep Neural Networks for Malware Classification


Jun 16, 2016
Kathrin Grosse, Nicolas Papernot, Praveen Manoharan, Michael Backes, Patrick McDaniel

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* version update: correcting typos, incorporating external feedback 

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