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L-RED: Efficient Post-Training Detection of Imperceptible Backdoor Attacks without Access to the Training Set


Oct 21, 2020
Zhen Xiang, David J. Miller, George Kesidis


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Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing


Oct 15, 2020
Zhen Xiang, David J. Miller, George Kesidis


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Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic


Nov 18, 2019
Zhen Xiang, David J. Miller, George Kesidis


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Notes on Lipschitz Margin, Lipschitz Margin Training, and Lipschitz Margin p-Values for Deep Neural Network Classifiers


Oct 15, 2019
George Kesidis, David J. Miller


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Revealing Backdoors, Post-Training, in DNN Classifiers via Novel Inference on Optimized Perturbations Inducing Group Misclassification


Aug 27, 2019
Zhen Xiang, David J. Miller, George Kesidis


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Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks


May 13, 2019
David J. Miller, Zhen Xiang, George Kesidis


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A Mixture Model Based Defense for Data Poisoning Attacks Against Naive Bayes Spam Filters


Oct 31, 2018
David J. Miller, Xinyi Hu, Zhen Xiang, George Kesidis


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When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time


Jun 28, 2018
David J. Miller, Yulia Wang, George Kesidis


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Detecting Clusters of Anomalies on Low-Dimensional Feature Subsets with Application to Network Traffic Flow Data


Jun 10, 2015
Zhicong Qiu, David J. Miller, George Kesidis


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A quantum diffusion network


Aug 11, 2009
George Kesidis


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