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02/04/2020
Minimax Defense against Gradient-based Adversarial Attacks
State-of-the-art adversarial attacks are aimed at neural network classif...
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11/18/2019
Privacy Leakage Avoidance with Switching Ensembles
We consider membership inference attacks, one of the main privacy issues...
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10/09/2019
Membership Model Inversion Attacks for Deep Networks
With the increasing adoption of AI, inherent security and privacy vulner...
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02/19/2019
A Random Subspace Technique That Is Resistant to a Limited Number of Features Corrupted by an Adversary
In this paper, we consider batch supervised learning where an adversary ...
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12/08/2018
AutoGAN: Robust Classifier Against Adversarial Attacks
Classifiers fail to classify correctly input images that have been purpo...
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03/31/2016
Extending Detection with Forensic Information
For over a quarter century, security-relevant detection has been driven ...
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10/13/2014
Multi-Scale Local Shape Analysis and Feature Selection in Machine Learning Applications
We introduce a method called multi-scale local shape analysis, or MLSA, ...
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06/03/2013